website-based career guidance system tailored for industrial design. When comparing ..... The first outcome would be a holistic view of career and career success. This ...... http://www.borbelytiborbors.extra.hu/ZSKF/CareerDevelopment.pdf.
Design for Career Success: Web-Based Career Guidance Model For Industrial Designers
Mark T. Williams II Master of Science in Industrial Design 2018
Design for Career Success: Web-Based Career Guidance Model For Industrial Designers By Mark T. Williams II
Thesis Submitted to the University of Houston In partial fulfillment of the requirements For the degree of Master of Science in Industrial Design 2018
Thesis Committee: EunSook Kwon, PhD Gordon Vos, PhD Mark Kimbrough
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Design for Career Success: Web-Based Career Guidance Model For Industrial Designers
__________________________________________________ Mark T. Williams II Approved by Committee Members:
________________________________________ Chair of the Committee Dr. EunSook Kwon, Professor and Director Department of Industrial Design Gerald D. Hines College of Architecture and Design
________________________________________ Dr. Gordon Vos, Adjunct Faculty Department of Industrial Design Gerald D. Hines College of Architecture and Design
_________________________________________ Mark Kimbrough. Assistant Professor Department of Industrial Design Gerald D. Hines College of Architecture and Design
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Abstract It was hypothesized that a more effective career guidance model could be created than the current print-based, computer-assisted, and internet-based models, which rely heavily on assessment. The premise of the researcher’s hypothesis is that with a more effective guidance model, students would have a more accessible, efficient and effective guidance that would foster higher rates of career success. For the development of such a model, a Participatory Research Methodology and Evolutionary Development Loop used for the development and testing of a solution was created, having been inspired by the Observe, Orient, Decide, and Act (OODA) Loop used by the US Armed Forces. During the literature review of existing models of career guidance, it was identified that assessment in almost any capacity was the main cause of career failure. When comparing various university career guidance systems, it was found that the most effective models omitted assessment, instead focusing on accessibility of career information. This trend lead to the creation and testing of a website-based career guidance system that did not include assessment in its model. The purposes of this study are to: identify the major factors of career success, develop an alternative and more effective model of career guidance, provide a career guidance system for industrial design students. To develop a viable test prototype, it was necessary to research and define the career field of industrial design. From this a job search methodology was created and tested which provided the backbone and inspiration for DesignerMi, the first version of the website-based career guidance system tailored for industrial design. When comparing DesignerMi to the existing models it was found that the developed system increased effectiveness, efficiency, and accessibility by over 99.7 % consistently in all testing groups. The effectiveness of this system was tested through a comparative study of existing models with DesignerMi using a task-based comparative analysis and three test groups consisting of 5 random volunteers per group ranging from freshman to alumni industrial design students. Research and testing on usability, funding for upkeep and system redesign, and an experienced web designer or design team are recommended for further development following the conclusion of this study. Keywords: OODA Loop, Career Guidance, industrial design, Computer-Assisted and InternetBased Career Guidance System
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Table of Contents Abstract ..................................................................................................................................... iii Table of Contents ...................................................................................................................... iv Chapter 1: Background and Problem Definition .......................................................................... 1 Introduction ............................................................................................................................. 1 Problem................................................................................................................................... 2 Methodologies ......................................................................................................................... 4 Significance of Research ....................................................................................................... 12 Chapter 2: Literature Review .................................................................................................... 14 Career Guidance Models....................................................................................................... 15 Issues of Models of Career Guidance ................................................................................... 19 Employment .......................................................................................................................... 21 Causes of Unemployment ..................................................................................................... 23 Industrial Design ................................................................................................................... 27 Chapter 3: Design and Development of Research .................................................................... 36 System Development ........................................................................................................... 49 Prototype............................................................................................................................... 49 Chapter 4: Testing and Evaluation of DesignerMi ..................................................................... 54 User Testing .......................................................................................................................... 54 Analysis & Update ................................................................................................................. 57 Chapter 5: Discussion ............................................................................................................... 62 Verification of Hypotheses ..................................................................................................... 62 Study Limitations on Testing ................................................................................................. 63 Study Limitations on Development ........................................................................................ 63 Future Opportunities.............................................................................................................. 65 Chapter 6: Conclusions............................................................................................................. 68 References ............................................................................................................................... 69 Acknowledgements................................................................................................................... 71 Vita ........................................................................................................................................... 72 Appendix A: Research Materials ............................................................................................... 73 Appendix B: Group Summaries and Data ................................................................................. 81
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Appendix B: Group 1 Summary and data .............................................................................. 82 Appendix B: Group 2 Summary and data .............................................................................. 96 Appendix B: Group 3 Summary and data ............................................................................ 110 Appendix C: Concept .............................................................................................................. 124
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Chapter 1: Background and Problem Definition Introduction Success in career is much like success in life, lack of access to resources can lead to hardship, and this can be especially impactful with regards to a person's career. Resources and access are the cornerstones to success in this world; and that which holds true for life also holds true for a career. During the 2006 London Design Festival, former Prime Minister Gordon Brown addressed and captivated his onlookers and visitors when he spoke: “Success does not happen by accident, it happens by design” (Brown, 2006). Since then the quote has found its way onto the lips of many CEO’s, blog enthusiasts, web pages, and social media posts. This idea that success is designed, much like a product or system brings the design of success into the realm of possibilities for designers to innovate and thus solve issues or problems related to success. As the definition and ideas of success are multifaceted a focus on a singular realm of success might shed light on other designable solutions to other realms and definitions of success. Student career success is directly related to an individual's ability or inability to solve the problems presented to them, be it job location, career information, or understanding of job specific skills. The person’s access to methods and mechanisms to address these issues can have either positive or negative effects on student career success. Additionally, the ability of students to locate such opportunities is directly correlated with the effectiveness of an institution's career guidance model. Problems with the existing methods of career guidance known as print-based, computer-assisted,
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and internet-based (Robinson, Meyer, Prince, Mclean, & Low, 2000) models will be reviewed to discover if a better model can be designed with better defined as improved accessibility, effectiveness, and efficiency.
Problem Design is the purpose, planning, or intention that exists or is thought to exist behind an action, information, material object or a system. A design is determined effective or a good product when the needs of both consumers and end-users are used in its planning, creation, and implementation (where consumers are defined as those who are purchasing goods, and end-users are defined as those who are using the product). The print-based model of career guidance became obsolete at the rise of the information age, because while consumer needs were considered, the needs of its end users were neglected and in relation to this study end-users and students will be used interchangeably. The failure of the print-based model was catalyzed by an increased use of technology by end-users whom would normally utilize the print-based career guidance model. Its demise was further cemented in its requirement for travel to and from the location that housed the material. Material, which in a technologically driven society becomes outdated shortly after it is printed. The inefficiencies of computerassisted and internet-based models of career guidance arise from their issues of access, informational relevancy, existence of informational overload and inability of endusers to locate career information. Career information is defined in this research as: information, data, links, job postings, internship postings, occupational titles, hard skills, soft skills, proficiencies, etc., that are directly related to a career and ability to locate and
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succeed in a set career. In all three models the issue that has had unilateral effect on end-users and thus affecting the goals of each model’s consumers is assessment. The role placed on assessment in each of these was a major cause of career guidance inefficiencies. All of which have a detrimental effect to students’ career success. Success in this study is dictated by students’ or recent graduates’ abilities to locate career information such as viable occupational titles, industry requirements, and methods of locating individually relevant jobs. Currently these key components are obstructed by the current models. Furthermore, when viewing the evolution of career guidance systems, their limitations were created due to misinformation and the misrepresentation of career success as only measurable in an educational environment. This view is perceived to have caused the issue regarding the role of assessment within career guidance systems, thus causing a prioritization of assessment over other factors of career guidance such as access to relevant career information, job location, and career skills. For this reason, the purpose of this project is to develop a new Website-based Career Guidance model. The first version of this model will be tailored to industrial design students with its title being DesignerMi. DesignerMi will address the current issues of the existing career guidance models for industrial design students by acting as a career aggregator placing all the necessary information needed for an effective career guidance system on a single website.
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Methodologies The methods used in this research were tailored to the researcher’s propensity for verbal communication, following a: speak, record, listen/transcribe, and research or “SRLR” loop, as illustrated in Figure 1.1. This process was inspired by the researcher's knowledge and practice of a methodology developed by military strategists and utilized in the US Armed Forces. Known as the “OODA” loop (Observe, Orient, Decide, and Act), it is a decision cycle that breaks down the actions of users into four steps allowing for expedient adaptation or change in the face of unknown (Boyd, 1995). This custom SRLR loop was then further modified into the Ask, Observe, Research, and Act Loop (AORA) participatory research methodology. This progression starting with speaking and allows for those with a knack for verbal communication and presenting to get an idea or concept out, which is beneficial for those who may lack the ability to write down concepts as articulately as they can speak them.
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Figure 1.1: The SRLR Loop. A methodology for investigation and research that facilitates effective decision-making. (Source: Inspired by the OODA Loop: Boyd, 1995)
“Recording” the idea allows for the originator to replay what was spoken and to “listen” to the concept as an observer and critique the verbiage, content, and idea itself. As it can be a daunting task to get outside of one's own head, this method allows for the viewing of an idea objectively which aids in concept refinement. Following the listening and transcribing phase; conducting “research” into the viability, precedence, and supporting factors of the idea can then be conducted by viewing the original idea as a tangible topic of inquiry. The results were the adoption of the Pragmatic Worldview and the view and the development of the concept that; the existing career guidance models and systems were inefficient from an end-user perspective. The combination of these equates to an understanding of career guidance models being poorly designed products with room for improvement. Therefore, approaching the issue of failed career guidance models and
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their major short comings could solve issues of career failure as they relate to career success By use of the pragmatic worldview and the developed research methodologies, it was discovered that the existing models were inefficient from an end-user perspective. From a product standpoint, the current models of career guidance are in theory designed for student career success; yet they only consider the consumers of the models, who are the institutions and career counselors. Developed to give career guidance personnel more efficient methods of helping students; they require and utilize assessment majority of the time and require the presence of a career guidance counselor which places students at a disadvantage. If models of career guidance continue to be designed without regarding the everchanging needs of its end-users only considering the consumers of the model, then it is bound to fail in the long term. Without the assistance of a facilitator or access to the assessment results and test; students are left to circumvent the unfamiliar career environment alone or not at all and are thus destined for higher rates of career failure. Guiding Questions
1. What if assessment was secondary or tertiary to access and information, or omitted entirely? 2. What If the system could be developed that didn’t require career guidance personnel, but could be utilized by them for a more effective and efficient model of career guidance? Through pragmatism these questions were answered by simply approaching the issues and their causes and effects by always viewing them as or asking; “what if they are true?”
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Pragmatism Pragmatism as described by Hookway (2016) is a laboratory philosophy, one that is centered on a concept that provides guidance on the creation and testing of theories and hypotheses. Best used “when performing experiments or tests, in the expectation that if the hypothesis is not true, then the experiment will fail to have some predetermined sensible effect” (Hookway, 2016). By use of a pragmatist worldview all the information required for creation and testing of this study’s hypothesis could be located. In Pragmatism, researchers “receive clarity by reflecting on the experiential consequences [they] would expect [their] actions to have if [their] hypothesis were true or if the concept applied to some accessible object” (Hookway, 2000). Pragmatism, allows the researcher to focus on the method best suited for the problem; “pragmatic researchers therefore grant themselves the freedom to use any of the methods, techniques and procedures typically associated with quantitative or qualitative research” (Europe, 2009). With a pragmatic approach different techniques can be utilized in unison or in serial. With pragmatism, it’s possible to conduct face-toface interviews, followed by focus group testing, and then utilize the results of the interviews and testing to construct questionnaires for the measurement of attitudes in a larger sized sample, upon which you can then conduct statistical analysis (Europe, 2009). Therefore, a key benefit of a pragmatic worldview is that through its use you can transform qualitative data into quantitative data (Europe, 2009). Research Methodology In pragmatism, it is common practice to utilize or create a variation of a participatory approach to research, which was in this case combined with the OODA
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loop to create the AORA (Ask, Observe, Research and Act) chain of participatory research. Figure 1.2 displays the AORA research methodology developed by this study.
Figure 1.2: AORA Loop – An Ask, Observe, Research and Act participatory research methodology, developed for this research activity. (Source: Inspired by Pragmatism, Hookway, 2000)
The participatory research model also known as an advocacy approach to research is an approach generally used when approaching the needs or issues of marginalized demographics, such as students of the University of Houston's industrial design department. Furthermore, this approach is possible because in a participatory methodology, “researchers are sometimes members of the group they are studying or have something in common with the members of the group”, (Europe, 2009) much like
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the researcher of this study, whom is a current Graduate Student within the mentioned department. This methodology is one that focuses on bringing “positive change in the lives of the research subjects” (Europe, 2009). Unlike other methods, a neutral stance is possible, but it is not a requirement and often times are done from a non-neutral stance. Non-neutral stances are often criticized in other methods because of their non-objective nature. However, “it is necessary as otherwise the thoughts, feelings or behavior of the various members of the group could not be accessed or fully understood” by both the researcher and audience of the research (Europe, 2009).
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Employment Search Methodology From earlier findings the method of searching for career information shifted from looking based on the view of industrial design being an occupation to one of it being a Degree as well as a career. During the research, while using and locating the most effective job search sites based on the number of job posts that came up for certain industrial design related search words, it was discovered that the most effective sites for searching in Texas were Indeed, Monster, and LinkedIn. There were other notable sites for the industrial design field like Core77 and the IDSA page, but when selecting Texas in particular the results were limited. As the search continued an additional site called internships.com, which is a part of Chegg.com also provided a high number of results. When using these sites, the original search term used was industrial design, however the focus on the post that came up was not the original title but the education or the degree these posts were asking for. By viewing posts based on the required education, the career field expands and allows for the location of Occupational Titles. Furthermore, by looking and cataloging what skills, proficiencies and other terms were occurring most often during this search methodology, the findings provided Occupational Titles, Hard Skills, Soft Skills, Proficiencies, and Personality traits. As the study and solution progressed the importance on the personality traits were omitted as that falls under the assessment sector of career guidance, which for this study will not be addressed.
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Hypotheses of Study There are multiple hypotheses associated with this study, including ones ranging from perspectives of career guidance models, interaction with students, and accessibility of the models. Following along with the Guiding Questions presented earlier, an approach which limits the roles and necessity of assessment and career guidance personnel aided in the creation of various hypotheses. The first hypothesis is that existing models of career guidance do not approach career success from a holistic viewpoint. This essentially means that due to a false or ambiguous definition of career and career success; current systems of career guidance cannot effectively provide guidance nor address key factors of career failure. A second hypothesis of this study revolves around the suspicion that models’ inefficiencies stem from the prioritizing of assessment over career success and job and internship location. What is meant by this, is that by focusing on assessment over more important and functional components of career guidance, users of current career guidance systems will be less likely to find career success. Thirdly, it is hypothesized that assessment is not required for career success and causes ineffectiveness in career guidance systems. The significance of this is that should a career guidance system be developed that prioritizes other factors over assessment or omits assessment all together; this new system would be much more effective than existing systems. The fourth hypothesis is that shifting to a system based on career information, employment opportunity location and ease of access to each of these will solve current inefficiencies. This means that a focus on those factors instead of assessment would
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ideally solve the current inefficiencies of career guidance and provides a more effective model of career guidance. Possible Outcomes of Study In this study should the hypotheses be proven true the outcomes of each would lead to multiple innovations in the world of career guidance positively effecting student and recent graduate career success. The first outcome would be a holistic view of career and career success. This would mean a redefining of each with a new understanding of the role career guidance would play in them both. The second outcome would be the creation of a career guidance model centered on guidance through access to relevant career information, career skills, and employment location. This outcome would be the most useful in regard to the research and its application for educators, students, and administrators. Furthermore, should the second outcome come to fruition the third outcome would be the development of a career guidance model that is more accessible, effective, and efficient than existing models. As part of the research will require of findings and proof of concept, a final outcome of this study will be a prototype or framework for a career guidance system for industrial design students and graduates.
Significance of Research To address the student need of employment on a large scale, a look at a micro occurrence of this problem is hypothesized to provide methodologies and models that solve the greater issue. As such, a comparison study of current models and viability of a
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new model will be conducted at the University of Houston, by focusing on students within the industrial design program. At the University of Houston, students have access to a system of career guidance known as Cougar Pathway, which is based on the computer-assisted career guidance model and relies heavily on interaction and use of career guidance counselors and personnel. Though this system was created for the University of Houston’s students and alumni to aid in the location of employment opportunities; no formal system of career guidance exists for the University of Houston’s students majoring in and entering an industrial design career. Despite this program existing within the university since 2003, producing graduates who went to work for companies like Lamborghini, Dell, Google, and HP; bringing countless publicity and design awards to the University of Houston. The industrial design department has only recently attained a university appointed career counselor during the 2016-2017 academic years. This means that while the majority of the University's students and graduates have had access to a system that addresses student employment needs, industrial design students, past graduates and their new career counselor are at a disadvantage. The current model of career guidance does not address the needs of the industrial design department and fails to address the needs of its students. Therefore, a career guidance model capable of providing for their needs are hypothesized to open new realms of development to foster universal student career success.
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Chapter 2: Literature Review State of the art publications on career guidance illustrate that it is a culmination of assessment methods, career information, guidance technique, and access to resources. Assessment itself does not equate to career guidance therefore assessment does not equate to career success and if this is true, then it is possible for career success to be achieved without Assessment. Career success has been shown to be associated with career information, guidance, and access; all of which are correlated with positive rates of employment, as opposed to simple assessment, which has a higher association with career failure. As reported by Ross et al., 2008: “college students, regardless of year in school, often deal with pressures related to finding employment” (Ross et al., 2008). Major causes of student career failure are related to the factors of unemployment, as career failure is equivalent to failing to gain employment within a desired field, major, or interest. Such failures are hypothesized to be caused by inefficient career guidance models. Factors related to student unemployment could potentially be solved with the creation of an effective career guidance model. If career guidance continues to fail, then an increase in student career failure may occur. However, career guidance issues are addressed, and a more successful career guidance model can be developed, then student issues related to unemployment may be solved, and needs related to employment are provided for, and students have higher chance of experiencing career success.
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Career Guidance Models Career guidance is the mechanism by which student employment needs are traditionally dealt with and is divided into three different models. Current models of career guidance include: print-based career guidance, computer-assisted career guidance systems and internet-based career information and assessment (Robinson et al., 2000). These three models are used as the bridge between career assessment and career information, with the traditional models of career assessment being used to “link clients to career resources, such as books and other print material, following an initial evaluation of the clients’ interests, needs, and values” (Robinson et al., 2000). In the last few decades a shift in models occurred in reaction to the many changes in the roles of technology in student’s everyday lives. This shift has since made print-based models obsolete, as this model relied on the collection and storage of career resource data, such as, “occupational information produced by professional organizations and government agencies” (Robinson et al., 2000). Leading to the creation of resources like The Dictionary of Occupational Titles (U.S. Department of Labor, 2003), where classification and a coding system for occupational titles categorized career information within its pages. The tables from “Mining the Internet for career information: A Model Approach for College Students” (Robinson et al., 2000), presents the advantages and disadvantages of each model regarding both career information (Table 1) and access mechanisms (Table 2).
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Table 1: Advantages and Disadvantages each model’s method for presenting career information Provides the advantages and disadvantages of how print-based, computer-assisted and internet-based models provides and presents career information. (Source: Robinson et al., 2000)
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Table 2: Advantages and Disadvantages each model’s access mechanisms - Provides the advantages and disadvantages of how career information is accessed in the print-based, computerassisted and internet-based models. (Source: Robinson et al., 2000)
Figure 2.1. presents a summarization of the disadvantages of each model as presented in Tables 1 and 2. The unique and overlapping inefficiencies presented with each model can be seen with the overarching factors being depicted in the center. Users of current systems are faced with informational overload when they are bombarded with too much information either via the internet-based or print-based models. This issue of informational overload is also compounded when the reliability and relevance of the information is in question through use of either the Internet based and computer assisted models when no career counselor is present.
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Figure 2.1: Summarization of overlapping inefficiencies of current - Provides a view of all the individualized and overlapping issues presented in each of the current models of career guidance. The three models are print-based, internet-based Model and computer-assisted career guidance (CACG) systems. The center most section provides a view of how the key components of career guidance were selected for this study. (Source: inspired by Tables 1 and 2 from Robinson et al., 2000)
When viewing the overlapping issues of computer-assisted and print-based, the include the requirements of travel, career service and career guidance personnel, the risk of information becoming quickly outdated, and issues of multicultural relevance, all of which hinder the success of each system. During an in depth look at these issues
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and inefficiencies the key things that model failure is centered on are: assessment, information, access, and guidance. Access is extremely important as it encompasses the other three, because access to information, access to job postings and travel requirements all play an immense role in career success. In this study, career success is defined as: understanding of the connection between major and career, career and occupation, and means of efficient access to relevant career information. This understanding is something that students and recent graduates can utilize for wise decision making when selecting an occupation. This definition presents three key areas for defining of career success and effective career guidance: accessibility, information, and guidance.
Issues of Models of Career Guidance Currently, most systems of career guidance only consider the career in relation to education, falling short of the holistic view of which includes pre-and post-graduation. They are meant to provide occupational information for major selection or to sponsor career success within the educational environment. Systems like the one developed at UC Berkeley, the Career Exploration Links (CEL) system (Robinson, 1999), which began as a project of the career and educational guidance library. The CEL system was traditionally a print-based career library, which provided information services to students as part of the counseling and psychological services. The CEL system’s “primary database contains a table with records for close to 1,000 nternet sites that provide occupational information or information about graduate programs” (Robinson et al., 2000).
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The CEL system’s “smaller, secondary database contains information about UC Berkeley undergraduate majors, including links to departmental homepages” (Robinson et al., 2000). However, this style of system is just one of the models used for providing career information and does not holistically address career success. Given a career and advancement within that career does not end with enrollment or attainment of a degree, systems that act as a bridge between education and industry or student and occupation need to be developed. The issues presented within the current models (as previously shown in Figure 2.1) illustrate that there are 4 components at play in career guidance models, and that findings have pointed to assessment as the primary cause of failure. Assessment is mentioned specifically in all current models regarding their deficiencies. Findings from prior research note the possibility of test anxiety arising during assessment, issues regarding the length of time before assessment results are received, and there being no direct link between the assessment and information provided. These factors have led to this study’s hypothesis that assessment is the failing component of current career guidance models. computer-assisted career guidance systems provide limited options for engaging users in assessments and share the issue of requiring human intervention for assessment utilization that is also shown in the print-based model. It also shares a deficiency of having issues regarding the reliability and validity of their respective assessment and information with the internetbased model. The internet-based model shares many of the assessment issues of the others, however it is alone in its issue with its methods of emotional assessment. Given the findings of this literature review on the methods of career guidance,
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those models that disregard assessment and its deficiencies while focusing on solving issues associated with access, information, and guidance are those that are hypothesized to be most well adapted and present an innovative design over existing models.
Employment This study defines employment as: the attainment of a paid or unpaid internship or occupation and is one of the key factors of career success. Career success which requires an understanding of the connection between major and career, as well as career and occupation, can be considered as an effect of employment. Occupation which is traditionally defined and interchangeable with the term job: is, “the activity by which one regularly makes a living…[or] a person's business or profession.” However, an expansion of the definition of occupation into “a complex dynamic involving individuals and their purpose behavior, within environmental contexts” (Wu & Lin, 1999) allows for more a holistic view of an occupation and its roles within a career. By using this expanded definition of occupation as presented in “Defining Occupation: A Comparative Analysis,” the concepts of occupational form and occupational performance, the consideration of a larger spectrum of inefficiencies with current views of success are possible (Wu & Lin, 1999). Occupational form, “the objective pre-existing structure or environmental context that elicits or guides subsequent human performance (Wu & Lin, 1999),” is one of the causes of confusion regarding what career success is. Composed of objective features such as “materials, human context and other characteristic of the physical setting,”
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occupational form also includes “socio-cultural dimensions that affect one’s perceptions and interpretations of the actions taken there” (Wu & Lin, 1999). These socio-cultural and physical setting components provide a medium for addressing issues of environments and views of them within the career environment. The environments of organization, education, athletic, and occupation can be viewed as smaller environments within the larger career environment, which exist both as overlapping and individual environments. Occupational performance, which is, “the action elicited, guided, or structured by the pre-existing occupational form (Wu & Lin, 1999) is more easily understood as the job or occupation itself. It is also “described as the doing, the action, the active behavior, or the active response exhibited within the context of an occupational form” (Wu & Lin, 1999). In the current understanding of career success, the career environment is seen as the educational environment, with performance based and assessed on grades instead of student employability and likelihood of success in a specific occupation. It should instead have focus on and consideration of the industry specific environment. Medically, occupational form is a hospital, while occupational performance refers to the skills used and the task that an occupation is based around such as a surgeon or a staff member within the hospital. Following along with the previous description of the medical field, a career “was traditionally associated with paid employment and referred to a single occupation” (Phifer, 2003). It has had an ever-progressing definition to now be seen, “as a continuous process of learning and development… a career includes all the roles you undertake throughout your life: education, training, paid and unpaid work, family,
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volunteer work, leisure activities and more” (Phifer, 2003). This definition will be the one used for this study, instead of the current definition that views career success as occupational success as assessed success within the educational environment. In order to innovate career guidance, the inclusion of success must be added to the current narrow perspective of career environment as only including the educational environment. This means that a further expansion of the definition of career success must be established. For this study career success will be defined as: an understanding of the connection between academic major and career, career and occupation, and the capability of efficient access to relevant career information which students and recent graduates can utilize for decision making when selecting an occupation. For students, occupational selection should be differentiated from selection of a major, because selecting biology-pre-med does not mean your occupation will be that of a biologist applying research solely to medical related projects. It would instead mean that a major and education in biology would prepare you for one of many occupations that require an understanding of biology. Specifically, attaining a major in industrial design may prepare a student for placement within a multitude of occupations, which means that the knowledge of those occupations is an important component of career information. Therefore, when developing a new model for career guidance focused on career success, an understanding of the components of occupational titles is required.
Causes of Unemployment With unemployment and the issues surrounding it being major causes of student inability to meet the need of employment, understanding and addressing factors that
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cause unemployment may allow for further development of a solution. Per an oxford study on economics, which goes into the many factors of the economy and its failures or successes; the issues and causes of unemployment are attributed to one of five reasons. These five include: frictional unemployment, structural unemployment, classical/ real wage unemployment, voluntary unemployment, and demand deficient or cyclical unemployment (Pettinger, 2015). Frictional Unemployment Frictional unemployment is a natural and recurring phenomenon in all economies, as it is related to the overall time it takes for workers or graduates to find, move between or change jobs. This is caused by lack of access to information on job markets and employment options. Structural unemployment is defined by a mismatch in skills within the labor force (Pettinger, 2015). Classical unemployment is the occurrence of a surplus of labor, caused when the wages for a certain occupation are kept above the market wage rate (Pettinger, 2015). Voluntary unemployment occurs if the benefits to remaining unemployed are greater than those that can be gained if employed. The final cause is a demand deficit, often caused by a recession or economy decline. It would be foolish to attempt to solve issues based in the realm of economic reform or economy stimulation, nor is a solution plausible to attempt to impact issues of social laziness or lack of incentive and motivation. The issue of classical unemployment is not addressable unless a unanimous compromise and standard pay scale is set with industry wide approval. As this is an idea that goes against the ideals of American capitalism and free tradetoobe , is thus seen as improbable solution. This leaves only the factors of frictional and structural unemployment to be addressed by this research.
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Study. Because solving frictional unemployment can solve the issues related to structural unemployment, the research focus will be on the frictional unemployment and its effect on career success.
Effect of Frictional Unemployment Frictional unemployment, which is caused by issues related to access and informational relevance, has grown exponentially leading to informational overload (Robinson et al., 2000) making it difficult to efficiently locate career information. In 2010, Google estimated that 300 Exabytes of man-made information existed, “and that more information was created every two days than had existed in the entire world from the dawn of time to 2003” (Zane, 2015). This increase in information and the level of access has completely changed the dynamic and role of traditional educational systems such as career services and career guidance systems. This upsurge in technology and information has caused one of the main models of career guidance known as printbased model to be rendered obsolete. This occurred because students of today have access to more information from their smartphones than past career guidance personnel, professors, and academics had access to in past university archives over the entirety of their careers. Technology’s Effect on Information, Access, and Education Technology continues to change the role and dynamic of universities as “massive open online courses, or MOOCs” become more widely utilized (Zane, 2015). In one study, the author detailed an experiment done by Jonathan Harber, who attended and received an education in philosophy from Harvard, Yale, and Stanford. Harber received
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the equivalent of a Bachelor of Arts in little over a year from a combination of the most well-known schools in the world, without ever stepping into a classroom. However, he did not attain a degree, as “the knowledge may [have been] free but the [diploma] costs dearly — but [Harber] was satisfied” (Zane, 2015) with the education and knowledge gained alone. Students are told that career success is directly related to the attainment of a degree, that through the education system it will be easier to find a job. Harber’s study teaches us that in this era students can get an education without receiving a degree with technology forcing educational institutions to adapt their models of education. Yet, their models of career guidance are lagging because though an education makes it easier to attain employment, attainment of a degree alone does not assist students in the location of relevant employment, thus making it an unsuccessful employment attainment mechanism. It is this that defines issues of employability related to the frictional unemployment, issues that correlate to the ability of students to access information. Currently it is possible to get an education without a professor in a traditional sense. Students can access information to get a college education without direct interaction with an educator. This is accomplished without out the quality of education being lowered, as online methods are just as effective and at times more effective than traditional models. When taking massive open online courses, the teacher is there as a resource to the content not as a necessity for course facilitation. The information would still exist and be accessible without teacher student interaction, though the teacher can aid in understanding and facilitation, their role is essentially secondary to a student’s
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access to information. This same logic, if applied to career guidance, can adapt career guidance models to modern methods of accomplishing educational and career goals. As the goal of career guidance is to guide students in their career, much like a map does, the presence of a tour guide or career counselor should not be the only means by which the users of a career guidance system can find their way. By understanding this, the development of a model that can be used without counselor intervention is enhanced and should in theory allow for the solution of several of the issues discussed in this review.
Industrial Design While looking for the issues within the career guidance models and attempting to identify methods for increasing student career success, research was conducted with a focus on the employment needs of industrial design students. industrial design was conceived during the rise of the Industrial Age (Heskett,1980), and has had many definitions as it evolved over the years to include more names, titles, required skills and proficiencies. Going from an occupation to a full-fledged career, industrial design has its roots through craftsman, which shifted to mass production of consumer goods, as well as into well designed, ergonomic, and appealing goods. This altered the manufacturing methods craftsmen once employed; moving them from a workshop to a factory setting. With the change of setting, role, and title came a change in education, skill requirements, and critical occupational proficiencies. This is not a change unique to industrial design, as many occupations have seen this evolution from occupation to
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career bringing changes not just within their industry, but within the models of how they train and acquire information. Industrial Design Employment The occupational requirements and performance of job tasks for industrial designers often requires that their focus to be on the needs of those outside the world of design, leaving the eyes of designers on everyone's problems but their own. However, as recent data depicts, industrial designers face a challenging future, thus methods of solving their employment need must be developed. The industrial design employment issue is especially true for Texas based industrial design students who are left with no relief from employment related needs. In Texas, from 2012 to the release of the most recent data in 2016, the number of employed industrial designers in Texas diminished from 2310 to 760 (27-1021 Bureau of Labor Statistic, 2016). If trends are to continue as they have been, with numbers dropping by half in yearly intervals; industrial designers will have gone occupationally extinct in Texas by 2025. This trend would not be as troubling if it was consistent throughout the US, in California for example the numbers increased from 3,950 in 2014 to 4,110 in 2015. Regarding these numbers, it is important to understand that these are not a reflection of a decline or increase in market demand for industrial designers or a decline in available occupations. They instead depict an issue in the ability of industrial designers to locate relevant jobs in Texas. If a shift from current means of career guidance were altered, with a focus on efficient access and relevant information as a means of career success and occupational selection, the decline in employment rates for industrial designers in Texas could be halted, leading to higher
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rates of employment and a subsequent reduction in industrial design student career failure. If a career guidance model which addresses these issues can work in Texas, which is considered the lowest common denominator of industrial design employment amongst other states with educational institutions with industrial design departments, then the overall employment level and industrial design student issues of employment would see positive changes across the country. Industrial Designer For the website-based career guidance model to be effective, the career being designed for must be defined, because too many variations of a career’s definition can lead to “informational overwhelm” (Robinson et al., 2000); a deficiency presented in the internet based and print based models of career guidance. The Industrial Design Society of America (IDSA) defines industrial design as “professional service of creating products and systems that optimize function, value and appearance for the mutual benefit of user and manufacturer” (“What is”, 2016). The United States Bureau of Labor Statistic (BLS) classifies the areas and occupation of Commercial and Industrial Design (C&ID) as one whose purpose it is to design, develop and manufacture products, across a broad scope of applications ranging across examples such as automobiles, furniture, home appliances, and children's toys (271021 Bureau of Labor Statistic). Listed under the occupational code 27-0000 and major category of Arts, Design, Entertainment, Sports, and Media Occupations, 27-1021Commercial and Industrial Design “combines artistic talent with research on product use, marketing, and materials to create the most functional and appealing product design.” (27-1021 Bureau of Labor Statistic, n.d.) Per the BLS, C&ID has 31,330 people
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employed within this field nationally. During the 29th assembly of the ICSID, International Council of Societies of Industrial Design, a newly agreed upon definition of industrial design was created. “Industrial Design is a strategic problem-solving process that drives innovation, builds business success, and leads to a better quality of life through innovative products, systems, services, and experiences” (ICSID, 2016). Merriam-Webster's Dictionary defines industrial design as “Design concerned with the appearance of threedimensional machine-made products; also: the study of the principles of such design. These are just a few of the many definitions used by varying organizations, companies, and definitions vary even more when looking at job and internship solicitations” (Merriam-Webster, 2016). These pre-existing definitions along with extensive literature review into industrial design classifications and an understanding of the varying roles that an industrial designer plays have allowed for the following definition, which is used by this study: Industrial Design: •
Is the professional service of creating products and systems that optimize function, value and appearance for the mutual benefit of user and manufacturer;
•
The creation and/utilization of products, systems, and information to solve needs and problems.
By providing a more holistic definition of industrial design, the career can be more easily studied allowing for location and quick access to occupational titles and its relevant skills. The first portion of the definition was leveraged from the IDSA definition, as IDSA works hand and hand with the many departments of industrial design across
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the country. Furthermore, a majority of students within this program are members of the Student industrial design Society of America (SIDSA), the student version of IDSA. By adapting and building from a definition that students are already aware of, a quicker adoption and understanding of the studies model and system is possible. The second portion of the definition, was developed based on the many occupational titles that were found during this research as well as desired skill sets for those occupations within an industrial design career. Skills and Proficiencies Often students and designers are faced with the task of explaining what someone with an industrial design education can do. Just as there has been confusion in what occupational titles they may hold, their capabilities can be considered just as diverse. This section will provide the Hard Skills, Soft Skills, Proficiencies and personality traits (HSPs) most often referenced or needed industrial design career success. Industrial Design can be considered as a profession which integrates a multitude of areas including: engineering (technology, techniques, material and processing), ergonomics (operation, safety, usability, sensation), business (marketing, management, planning, corporate identity), aesthetics (form, visualization, style), and even social, environmental, and cultural issues (Yang et al., 2005). The varied list of skills and abilities that industrial designers possess which may allow them to adapt to other occupations outside of an industrial design career is almost limitless. Someone in an industrial design career can specialize like other careers such as the many divisions of the Medical Field, Law, and Engineering. Their specializations include “product
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planning, design management, mechanism design, CA industrial design [computer assisted industrial design], interface design, etc” (Yang et al., 2005). Many of the titles previously mentioned, can also be made into a specialty, such as Human Centered, Automotive, and User Interface Design. In regard to the HSP’s needed for career success in industrial design and its related occupations, by researching the many job listings and compiling a list of the repeating skills and proficiencies requested, a current list of industrial design related skills was created. The following is a list of hard skills: which, “are specific, teachable abilities that can be defined and measured, such as typing, writing, math, reading and the ability to use software programs” (Staff, 2010). •
Sketching
•
3D modeling
•
Rendering
•
Prototyping
•
Model Making
•
Visual Communication
•
Presentation
•
Design Research
•
Project Management
•
Storyboarding
Additionally, skills known as soft skills are those that are “less tangible and harder to quantify [than hard skills] are things such as: etiquette, getting along with others,
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listening and engaging in small talk (Staff, 2010). The following is a listing of some of these soft skills: •
Public Speaking
•
Verbal Communication
•
Written Communication
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Problem Solving
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Entrepreneurship
•
Teamwork/Collaboration
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Leadership
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Emotional intelligence
•
Interpersonal
•
Time Management
Additionally, there are proficiencies which are the masteries “of a specific behavior or skill demonstrated by consistently superior performance, measured against established or popular standards.” •
Solidworks
•
KeyShot
•
ProE,
•
3Dmax
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Adobe Suites
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Sketchbook Pro
•
Digital Sketching
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•
User Interface
•
User Experience
•
Graphic Design
•
Storyboarding
•
Furniture (construction, material, production)
•
Manufacturing process (mold flow simulation, injection molding, etc.)
•
Home Goods/Appliance
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Branding
•
Materials and Finishes
There are also key personality traits that have been identified as associated with success, including: •
Confident
•
Team oriented
•
Attention to detail
•
Self-motivated
•
Creative
•
Self-starter
•
Problem solver
•
Multitasker
•
Ability to work autonomously
Though personality traits were found during the process of this study and are helpful to know, they will not be listed as a part of the current system development as they are more beneficial in assessment. As such knowledge of these traits would be better suited
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toward collaborations with career guidance personnel or as part of a self-assessment component of future variations. This list should be treated much like a living document as needs, skills, and requirements will change over time.
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Chapter 3: Design and Development of Research In this section a focus on the phases of the research and methods used to locate, evolve and develop this study’s model, methodologies and system are broken down into three phases. These phases utilize the SRLR and AORA loops mentioned earlier shown in Figures 1.1 and 1.2.; with the DTAA loop being used to Develop, Test, Analyze and Act on findings to continually and efficiently evolve the concept. Figure 3.1 illustrates and explains the DTAA loop.
Figure 3.1: DTAA Loop – Develop, Test, Analyze and Act loop used to attain and apply findings to continually and efficiently evolve a concept. (Source: Inspired by Pragmatism and Army After Action Review)
The DTAA loop adapts the participatory methods of pragmatism drawing from the researcher’s military experience and applied knowledge of the Army’s AAR system. The
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AAR or After-Action Review is a military method that collects sustains and improves following all and any military activity, movement, or training. This means that information on what when well regarding the event; as well as what went wrong and recommend methods of addressing issues are collected and applied before the next activity or attempt at the same event has begun. The interaction of the three utilized loops are presented in Figure 3.2 which depicts a completed research and development progression as well as the role and placement of each loop within the three phases of this study are illustrated.
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Figure 3.2: Thesis Phase Map – The SRLR method and the OODA method were combined to form the AORA method of participatory research developed and implemented by this thesis. This figure provides an overview of the entire process as it relates to the SRLR, AORA, and DTAA loop in regard to the entire study. These contributed to three main phases of this research: which sought to identify, investigate, and develop improved methods for career guidance. (Source: Developed as part of this thesis)
During the development of this system and its research, a committee member explained that: “Software is never finished, it is only released.” A saying accredited to notable computer scientist, Gerald Weinberg who pioneered ideas in the psychology and sociology of software development. It aided in the inspiration of the various models
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and developmental loops used in this study. From this understanding that a system and thus this research is never finished, as such the last phase never truly ends, and updates and alterations are intended to continue after this study’s conclusion. Phase 1: Identify Through the participatory model, possible research directions could be located by searching for overlapping areas of interest. Those areas were student career needs and whether or not institutions had an existing system for solving issues related to those needs. The justification behind using an institution’s existing system; is that by looking into existing systems or products, innovations can be made if issues and failures are present within an established system. This approach allowed for an evolution or an adaptation of existing systems, which would in turn reduce the number of steps for implementation and the learning curve for successful utilization. Phase 2: Investigate A Participatory study focused on industrial design students and the University of Houston following the selection of career guidance models and their issues as the focus of the study. Interviews, surveys and observations allowed for an understanding of how the career failure affected industrial design students. The issue of locating employment was a cause for major concern, as not only is it a universal issue for all students; for industrial design students it is a requirement for graduation. Though an institution may place priority on assessment-based guidance, literature review proved that there was “no direct link between assessment and information” (Robinson et al., 2000); thus, making assessment and its subsequent results non-essential or dispensable.
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Figure 3.3 illustrates the components of current career guidance models breaks up career guidance into the 4 categories of access, information, guidance and assessment.
Figure 3.3: Components of career guidance– Career guidance is an integration of multiple facets of student experience, including access to resources, information on career opportunities, guidance from counselors, and career assessment. (Source: Inspired by, Robinson et al., 2000)
When comparing other institution’s career guidance models, places like California and New York have always been hubs for creative people, each providing their students with information on design employment. This information is readily accessible by students and graduates. Institutions like Rhode Island School of Design, for example deals with the issue of access and relevant career information by releasing a list of industry opportunities and internships. Students can access more information on the university’s career services website and job search engine. These trends show that the available information on the employment market for industrial design students at other schools and regions is vital to career placement and success. Figures 3.4, 3.5, and 3.6. all depict the components of current career guidance models and a breakdown of the known inefficiencies within each.
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Figure 3.4: Components and inefficiencies of print-based career guidance – Provides a breakdown of the inefficiencies that exist within various components of print-based career guidance. (Source: Inspired by Robinson et al., 2000)
The print-based model is the oldest of three models of career guidance rivaled only by networking in its tenure. However, though networking is a key component and its own career guidance model very nature of networking requires and allows it to adapt per person per situation at any time or place. The print-based models’ title of the eldest also makes it the most obsolete in today’s technological driven society. Starting with its method of access, because all users are required to be physically present in the building or location of the resources. One’s ability to access resources becomes limited due to transportation, hours of operation, and informational expiration date limitations. Appointments must be made when trying to access certain resources, career guidance, and even assessment and assessment results. Given that
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the old models are based heavily on assessment, being unable to access and utilize the results of past assessment without direct intervention continued to pose even more complications on an already dated system.
Figure 3.5: Components and inefficiencies of computer-assisted career guidance – Provides a breakdown of the inefficiencies that exist within various components of computer-assisted career guidance. (Source: Inspired by, Robinson et al., 2000)
The computer-assisted model shares some of the same issues presented in the print-based model, including the requirement of travel, issue of outdated information, and its overabundance of assessment. It has the unique issue of either providing information that is too general or too vague, causing further complications for those seeking to improve chances of career success.
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Figure 3.6: Components and inefficiencies of internet-based career guidance- Provides a breakdown of the inefficiencies that exist within various components of internet-based career guidance. (Source: Inspired by Robinson et al., 2000)
The internet-based model also shares some similarities of the others with the most notable being informational overwhelm, which in this case is partially caused by lack of additional guidance within this model. Do to the nature of the internet and the current understanding of career guidance those left to their own devices have been told for years that assessment is a key factor in career guidance and career success. However, because they lack direction, users of this model will assume any assessment will do and thus the issue of reliability and validity of those assessments are major causes of concern and overwhelm in this model. Further research into the cause and effects of employment which will be expounded on in the Literature Review section of the research; allowed for an understanding of assessment as the root cause of issues with existing career guidance
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models. Figure 3.7 provides an explanation of an effective career guidance model taking into consideration the inefficiencies of the current ones. Though this section only offers a quick synopsis of the components’ chapter 2 goes further into each model’s issues.
Figure 3.7: Components an effective model of career guidance- Provides a breakdown of what components would be required of a career guidance model for it to be effective the required features based off the noted inefficiencies of print base, computer-assisted and internet-based models of career guidance. (Source: Inspired by Robinson et al., 2000)
Figure 3.7 represents what is hypothesized to be an ideal model of career guidance when addressing the issues of the currently utilizes models. Regarding access the elimination of travel requirements is a must, as for something to be truly accessible
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physical location should not be a hindrance. Through thisFurthermore, the appointment-based system is also taken out of the equation with a move toward a 24hour accessibility window being a key driver of the new model. As past systems required a membership or access to the organization that offered the system, a push for a base-line of universal access via internet enabled devices would mean that anyone with internet access could utilize the resources. For the information itself, a system that allows for easy and constant updates is necessary to avoid information becoming outdated. Informational overwhelm which is caused by sensory or mental overload do to a bombardment of too much information can be addressed via a presentation of information in smaller more digestible segments. The final segment of guidance should be shifted to one that offers effective assistances with or without human intervention but can become more effective when used alongside a guidance counselor. The method of guidance should not be rigid much like the computer-assisted model, but fluid and easily adaptable with information being general to all those interested in that particular career. Assessment in this model becomes a secondary feature instead of a primary requirement. With assessment seen as optional the focus can now be placed on job location and informational relevancy with any assessment done being used to enhance the model’s effectiveness.
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As a result of these findings in Phase 2, the study’s first hypothesis, which stated that a model’s inefficiencies stem from the prioritizing of assessment over career success and employment location, was proven to be true. The second hypothesis, that assessment is not required for career success and causes ineffectiveness in career guidance systems, was also proven to be true. These developments provided the justification to the next phase of this study, which were focused upon applying these findings to solve the understood issues. Phase 3: Develop Experimental Design Current effective systems of career guidance deal specifically with providing career information; allowing career services and job search engines to act as an addition to their models. As such the developed model will emulate the career information component, while also focusing on methods of locating employment opportunities. As University of Houston’s career guidance model fails to provide information or employment opportunities for the industrial design career, students are in need of a functioning career guidance system. As assessment is not a requirement of successful models of career guidance assessment will be omitted. In leaving out assessment, the developed model of this study allowed for the creation of a prototype of the system to be tested by industrial design students. During this phase a comparative analysis of existing model’s and the developed model was done, allowing for the collection and study of quantitative and qualitative data. Collected via survey methods, the test utilizes a combination of 5-point Likert scale and a qualitative questionnaire. Respondents, who are given equal opportunity and access to the study were tested on a first come first serve basis. Participation in the
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study was completely voluntary, with subjects participating randomly at their earliest convenience and availability. Respondents are then broken into test groups consisting of 5 students per group based on when they elected to complete the task and survey. During the prescribed time frame of the study 15 respondents or 3 test groups responded with 2 additional respondents providing feedback toward the end of the study. Test Development The purpose and the structure of this method of testing is meant to prove or disprove one or more Hypothesis; by allowing students to attempt their methods/existing model followed by the developed model, users were able to see a direct comparison of the two models without one affecting the results of the other. The original format of the test would have called for a separation of students into two groups. One group would be allowed to use the website-based career guidance system and the other would utilize the methods familiar to them. This was replaced with the current structure, because with the individuality of each user and their methods, the likelihood of bias or other factors affecting results were high enough to cause possible issues in testing. When discussing these factors with an expert on Human Factors, these issues were best rectified by allowing the users to utilize both systems, with their method being the first. This was ideal, because use and knowledge of the website-based career guidance system was hypothesized to become the preferred method of employment searching. This is problematic in the pragmatist context because if the hypotheses are true then it would in fact affect the study’s findings, which would hinder the comparison and data collected.
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At each stage, when a group is tested, findings will be used to update the system. Figure 3.8. depicts the evolutionary development loop developed for this study. This loop, which is a smaller component of the DTAA loop (previously shown in Figure 3.1), allows for the rapid and effective evolution and innovation of a system.
Figure 3.8: Evolutionary Development Loop –Explains the flow and interaction of activity and data as it aids in the continuous evolution of the studies system. (Source: Developed as part of this thesis)
The system evolves by fixing any issues found during testing, with innovations coming about through recommendations of users. As it has infinite evolutionary possibilities, the loop is depicted as closed but continuous.
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Website-based System Development This section covers the design and components of the website-based system. As the focus of this model is upon industrial design, the prototype website that was developed has been titled DesignerMi, which can be found at DesignerMi.com. The title of the website is indicative of the many variations to come and the important factors in its development. “Mi” stands for “My Industry,” which was used to reference the future universal application of this study’s findings, as it is meant to offer career success on a particular user's career industry or a student's major. Currently with industrial designers as the focus; DesignerMi offers a one-stop shop for all the career needs, education, and advancement for students and workers within the industrial design field. As research and results continue, EngineerMi for Engineering students, PetroMi for Petroleum Engineering students, and ArchitectMi for Architecture students are examples of future iterations that could be created.
Prototype DesignerMi can be broken into six key parts: Career Guidance, Occupational Titles, Hard Skills, Soft Skills, Proficiencies, and Employment Search Engines. Each of these components were identified and explained during earlier parts of this paper. However, as the career guidance component of the model is what underwent the most innovation from the traditional methods, some additional explanation on that topic is needed. Figure 3.9. Illustrates the information architecture and layout of the website as it was tested by users.
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Figure 3.9: DesignerMi information architecture - Provides a view of all the section of the developed website. Following a long a continuous scroll interface, users would move from through the sections in the following order. Introduction, Career Guidance, Occupations, Hard Skills, Soft Skills, Proficiencies, Employment and how to contact the website administrators. Each section would provide information and links to websites or educational content created via other platforms and sites (Source: Developed as part of this thesis)
The original plan for the career guidance section was meant to only house text for tips, tricks and notes for job searching; however, as testing continued the need and request for more than just ways of using job search sites were discovered. For example, it was identified that external links to other sites would be a good way to increase the scope of material available to users of the site. Thus, the design matured to serve as something of a career aggregator, such that DesignerMi includes information on the site itself, as well as the provision of links to external sites. Examples of such links include career guidance related material within YouTube videos, Lynda videos, and other educational
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content regarding industrial design, which allow students to quickly access career information from mixed media sources.
Evolution As the concept evolved the data gained during testing of the system was directly translated into updates for the developed website. Each phase of testing followed the exact same testing format and it was designed to allow for an understanding of how students utilized current models. The testing method also provided information that allows for a redevelopment of the study’s website to increase its effectiveness. The original testing phase called for a separation of the test and control group but following reevaluation of the system and end goals of the study the layout of the Task Based Comparative analysis was altered. The new task and test as it was explained to the students is as follows: 1. Task a. 20 minutes b. Using methods/models/systems you are personally knowledgeable of, locate as many career/personally relevant jobs/internships as possible within 20 minutes 2. Survey a. 5 minutes 3. Task a. 20 minutes b. Using the provided website, locate as many career/Personally relevant jobs/internships as possible within 20 minutes: http://DesignerMI.com/ 4. Survey a. 5 minutes 5. Follow Up Questions a. 10 minutes
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Students were given equal access and opportunity to take part in the study, and therefore none were selected, but all were random and volunteers. The survey was distributed via email, Facebook Messenger and other online communication methods. Appendix A provides the exact survey given to students with link to IRB approved consent form attached to the survey. Each testing group went through the same test, which included three phases of testing and the results of these three phases of testing are provided in Chapter 4. The following is a brief synopsis of the overall flow of the design’s maturation and evaluation. Phase 1 of testing was done on the initial prototype design and following collection of data from group one, the site was updated to include text for the occupational titles below the image, so that the titles were always displayed without needing to click the image. The creation and relocation of the career guidance section of the site came about from the findings, in order to assist students in using the site. As the data came in, one of the subjects mentioned that they used networking as their personal method. Though not a part of the current study it is important to note that networking was found in the earlier stages of research but was omitted as it was thought that there would be no method to design for networking in the information gap approach. The second phase of testing was then conducted, with recommendations from the second test group providing the idea for the addition of career guidance videos, to DesignerMi. Thanks to student recommendations professional designers, career guidance personnel, and professors were contacted to begin creating career guidance videos over various topics vital to career success. Additional updates made to the
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system centered on the alteration of the navigation bar. Traditionally they are along the top and travel with the page, but an attempt to have them along the side of the page was made. However, because users are familiar with the traditional navigation bar, DesignerMi will alter the sidebar to use a top search bar. Following the second design and testing iteration, a third test group in Testing Phase 3 reviewed the system. Recommendations and findings for the system update begin to echo findings of the previous groups, with no notable changes outside of the visual design of the website being mentioned. Due to lack of funding, the researcher’s knowledge and ability in web design being limited, the visual evolution of the site is recommended for later updates following the completion of the study.
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Chapter 4: Testing and Evaluation of DesignerMi User Testing The survey questions as well as the detailed data collected during user testing as discussed in this section may be found in the appendices of this document. This section serves to provide a concise and easily digested roll-up report of the findings, including test subject demographics, and percent of the vote from each demographic subgroup. Group one of the study consisted of two master’s students, two students who graduated after 2014, and one current senior. The most important factors to them were career information and Internships, each getting 80% of the demographic total vote, with Jobs getting 60%. Figure 4.1 provides a comparison of the existing model and DesignerMi focused on the total number of employment options located that were relevant to the industrial design career field and the total number of those that were relevant to individual user interest.
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Figure 4.1: Comparison of total career relevant and individually relevant employment opportunities located by Group One - Provides a view and comparison of all the data collected for group one with regards to the number of employment options located by the users that were relevant to the industrial design career field (Career Relevant). The second set of data presented (Individually Relevant) is based on the employment opportunities that were located that were directly relevant to the students’ individual needs and career interests. (Source: Developed as part of this thesis)
Group Two of the study consisted of two students who graduated after 2014, and one current junior, one current freshman, and one current master’s Student. The most important factors to them were Jobs and Internships, each getting 60% of the demographic total vote, with career information receiving 40%. Figure 4.2 provides a comparison of the existing model and DesignerMi focused on the total number of employment options located that were relevant to the industrial design career field and
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the total number of those that were relevant to individual user interest.
Figure 4.2: Comparison of total career relevant and individually relevant employment opportunities located by Group Two - Provides a view and comparison of all the data collected for group two with regards to the number of employment options located by the users that were relevant to the industrial design career field (Career Relevant). The second set of data presented (Individually Relevant) is based on the employment opportunities that were located that were directly relevant to the students’ individual needs and career interests. (Source: Developed as part of this thesis)
Group three of the study consisted of two seniors, one junior, one sophomore, and one freshman. The most important factors to them were Jobs and Internships, each getting 80% of the demographic total vote, with career information receiving 0%. Figure 4.3 provides a comparison of the existing models and DesignerMi focused on the total number of employment options located that were relevant to the industrial design career field and the total number of those that were relevant to individual user interest.
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Figure 4.3: Comparison of total career relevant and individually relevant employment opportunities located by Group Three - Provides a view and comparison of all the data collected for group three with regards to the number of employment options located by the users that were relevant to the industrial design career field (Career Relevant). The second set of data presented (Individually Relevant) is based on the employment opportunities that were located that were directly relevant to the students’ individual needs and career interests. (Source: Developed as part of this thesis)
Analysis & Update Due to the nature of the study and the demographics being tested, analysis of the data has been stratified by testing group, with average rankings provided for comparison of the existing model with the newly developed concept model. As previously discussed in Chapter 3 of this paper (Chapter 3: Design and Evolution of the New Model), testing of the existing and the new model was done in an iterative improvement design loop. Test groups included 5 test subjects per group, with varying
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demographics. As the task and survey was completed by each testing group, the data was analyzed and then the information gathered was used to make an update to the site, which was then subsequently reassessed in another iterative test (this included 3 rounds of testing overall). This section will present the summarization of the data found, summarization of survey responses, with completed surveys and graphs included in the Appendix. The explanation of updates and innovations made to the website at each stage were provided in the previous chapter. The desired overall sample size for the study was 20 or more, divided into the 3 testing groups. However, subject recruiting realities resulted in a smaller collection of 15 total subjects, with 5 in each group. There was a 4th group for which testing was attempted, however only two test subjects participated, resulting in too small of a number to be analyzed, thus the desired 4th group data has been omitted from this analysis. Findings thus far as well as the plan of action moving forward with group four and all subsequent groups and updates will be addressed in the section discussing recommended forward work for this study. Group One Summary When the findings are averaged together for each category, the research places the overall ranking of the first group’s existing model at 2.2 with the developed model ranking of 3.167; which provides an overall ranking increase from existing model to developed model of .967. Figure 4.4 provides a depiction of the comparison of rankings and data collected for each category tested in group one.
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Figure 4.4: Comparison data and ranking for Group One - Provides a view and comparison of all the rating data collected for group one with each category being rated from 0-5, where 0 was the least favorable rating and 5 was the best rating possible. Data was collected on the accessibility of career information (CI), accessibility of employment options, effectiveness of method a location CI, and effectiveness at locating employment options. efficiency of locating CI, and efficiency of locating employment options. (Source: Developed as part of this thesis)
Group Two Summary When all the findings are averaged together for each category, the research places the overall ranking of the second group’s existing model at 1.7 with the developed model ranking of 3.07; which provides an overall ranking increase from existing model to developed model of 1.37. Figure 4.5 provides a depiction of the comparison of rankings and data collected for each category tested in group two.
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Figure 4.5: Comparison data and ranking for Group Two - Provides a view and comparison of all the rating data collected for group two with each category being rated from 0-5, where 0 was the least favorable rating and 5 was the best rating possible. Data was collected on the accessibility of career information (CI), accessibility of employment options, effectiveness of method a location CI, and effectiveness at locating employment options. efficiency of locating CI, and efficiency of locating employment options. (Source: Developed as part of this thesis)
Group Three Summary When all the findings are averaged together for each category, the research places the overall ranking of the third group’s existing model at 2.67 with the developed model ranking of 3.63; which provides an overall ranking increase from existing model to developed model of 0.96. Figure 4.6 provides a depiction of the comparison of rankings and data collected for each category tested in group three.
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Figure 4.6: Comparison data and ranking for Group Three - Provides a view and comparison of all the rating data collected for group three with each category being rated from 0-5, where 0 was the least favorable rating and 5 was the best rating possible. Data was collected on the accessibility of career information (CI), accessibility of employment options, effectiveness of method a location CI, and effectiveness at locating employment options. efficiency of locating CI, and efficiency of locating employment options. (Source: Developed as part of this thesis)
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Chapter 5: Discussion The hypotheses, desired outcomes, and pragmatic approach of this study, as described previously, allowed for various issues and considerations to be addressed by approaching the study’s hypotheses as if they were true (somewhat contrary to the typical null-hypothesis approach). In dealing with various causes and effects associated with each hypothesis, the root cause of issues within career guidance was determined to be assessment, which stemmed from a limited view of career success based on historical decisions and perspectives of career guidance.
Verification of Hypotheses The first hypothesis, “existing models of career guidance do not approach career success from a holistic viewpoint,” was shown to be true through literature review and an analysis of various careers and their environments. The second hypothesis, “models’ inefficiencies stem from the prioritizing of assessment over career success and job and internship location,” was also demonstrated to be true during all phases of the model’s evolution, and additionally verified through testing and analysis. By omitting assessment, hypothesis three and four which stated: (3) “assessment is not required for career success and causes ineffectiveness in career guidance systems,” and (4) “shifting to a system based on career information, Employment Opportunity Location and ease of access to each of these will solve current inefficiencies,” were also both tested and were proven true at the conclusion of the
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study as shown in the results included both in the appendices of this document and throughout the various phases of this study.
Study Limitations on Testing This study called for a minimum of four groups, or 20 respondents: this minimum was not met. A total of 17 students, consisting of three full test groups made of five students each, with two recruited for the fourth group. Due to failure to attain the desired subject sample size for group 4, a continuation of the study and testing of the system with at least three more students would allow for additional review of the final model as developed in the course of this study.
Study Limitations on Development In the earliest iterations of the website-based career guidance system, an importance was placed on the identification and use of Application Program Interfaces (API) for various search engines. These API’s were originally used in creation of career specific search engines. Inspired by systems like Kayak and Expedia, which are topic specific search engines, the goal was to utilize the API’s of existing job search sites to create a new system that operated based on the study’s search methodologies using Occupational Titles, Skills and Proficiencies as search criteria. The search engine, which would have been the key feature of the new model of career guidance, was meant to work within the ecosystem created on the website. The original concept website provided a list of occupational titles, hard skills, soft skills, and proficiencies. The original concept and website also utilized a multi-page web model.
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Students would go from the home page to the Design page, which provided career information through links, which sent students to outside pages to learn more about specific occupations or skills. Once the career information page was explored and understood, users would then go to the next section, titled “My Profile.” The site was originally named DesignerMi for: design, my profile and industry. Design denoted the career that the career information was focused on. My profile, abbreviated “M” was meant for the creation of a user profile. The “I” which stands for Industry was meant as the landing page which housed the career specific search engine. The My Profile section originally would have housed a user profile and avatar creation system; that would have allowed students to input one to five occupational titles and one to five skills and proficiencies that they personally possessed and were considered a strength. Based on the job search methodology developed for this study, by selecting titles and individually relevant skills and proficiencies, opportunities that are located would be individually relevant. This filtering system would allow for the location of employment that users would be most successful in and that aligned with their career goals and skill sets. The next section of the site labeled “Industry” would be where the search engine was located and using the information from the Me section would locate and present the jobs relevant to the user. Though this direction showed promise, limitations on time, manpower, and funding for the creation of the search engine became secondary to the creation of the website and presentation of career information. The collected API’s however allowed for a new interpretation of the industry page, by way of providing links and explanations to
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the most effective search systems for the industrial design career. Future iterations of this or similar systems may still benefit from considering the inclusion of these search engine-based methodologies and content.
Future Opportunities System As the evolutionary developmental model is made for the continuous development of the website-based career guidance system, collection of data using additional test subjects and more varied demographics would allow for further innovation and evolution of the system. This additional testing phase, which would utilize the same or slightly altered testing methods than those explained in Chapter 3, would ideally consist of 30 test users. From the data found during the testing phases of this study, a new hypothesis of a website-based-career guidance system evolving and then adapting to other career fields was created, mainly that “the methods used for creating a system for the industrial design career field could be used to create website-based career guidance systems for other careers and industries with DesignerMi being used as a template.” Pursuit of this hypothesis in future work may benefit multiple student demographics and career trajectories. During testing, responses to the survey question: “What can be done to make DesignerMi more efficient and effective?” were collected. Recommendations were given to add career guidance videos over specific topics. Furthermore, end-users believe that reaching out to designers in the industry to provide career guidance tips in video format
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would provide greater value and resources for student use. Follow-up questioning and data has pinpointed that the first topics for career guidance videos should cover the following: •
Networking for design and creative fields.
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Resume building for design and creative fields.
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Portfolio creation and design considerations.
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Online portfolio tips, tricks, and recommendations
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Personal Branding for design and creative fields.
During the study, many respondents recommended replacing the list of employment search systems with a single search engine that utilized each of them. These recommendations bolster the ideas which guided the study’s original direction, and that original concept for inclusion of search engine APIs is worth pursuing in the future. In addition to further maturation of the system, possible avenues of funding such as the upkeep and creation of other websites are topics for consideration. Unlike the deficiencies of the historic internet-based model, which required constant upkeep, the newly developed website-based career guidance model would function as an aggregator. Therefore, it would only need to be updated periodically to add new content. However, issues may arise if the content that the site provides links to is deleted, corrupted, or crashes. The website's contact section will allow students to inform the researcher or future web-team of such issues. Research Additionally, a viable path of future study would be to assess student stress related to employment and career guidance issues using subjective rating scales. In
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future cycles of development, evaluation on levels of student stress pre- and post-use of the website based-career guidance could be conducted. Now that a solution to career guidance issues exists, it is possible to verify if dealing with that issue has a positive effect on student stress. Furthermore, a study on usability would allow for further evolution of the system for more effective user experience design, providing innovations that would provide students an even more effective or efficient model. Business Possible business models based on this system call for the marketing of the research and system to institutions of higher education. First step would be providing DesignerMi free of charge to institutions with industrial design departments to allow for comparisons of their systems to a website-based career guidance system. Step two would be the explanation of how the system can be adapted to other fields and majors. Once an institution selects which majors it would like a website designed for, fees for the development and creation of the requested site can be collected. This same model can be used when developing a solution to veteran and soldier career success, but instead of approaching it from a degree specific perspective, it would be done from a Military Occupational Specialty (MOS) perspective. Currently a discussion over the application of this research is being had with relevant military personnel on the adaptation of the system to fit military needs.
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Chapter 6: Conclusions It was hypothesized and demonstrated that a more effective career guidance model could be created, and that in doing so, students would have a more accessible, efficient and effective model that would foster career success. For the development of such a model, the Participatory Research Methodology was created inspired by the military’s OODA Loop. Hypothesis one was proven to be correct during multiple phases of the research. During the literature review and subsequent analysis of existing models of career guidance, multiple issues regarding assessment were identified, which showed hypothesis two to be correct. During the literature review-based comparison of existing university career guidance systems, it was found that the most effective models omitted assessment, with importance placed on career information, and verifying hypotheses 36. During the final phase of the website-based career guidance model, the issue of assessment was assumed to be true as dictated by the pragmatic worldview. This allowed for the creation and testing of a system that did not include assessment in its model. In other words, if the hypothesis was true, the omission of assessment would have a positive effect on student ability to locate information and attain career success. As the system worked as intended and provided a more accessible, effective and efficient model, all hypotheses were shown to be true. Therefore, continued future development and maturation of the study’s developed model is recommended, with additional testing and demographic expansion to other career fields in addition to industrial design.
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References 27-1021 Commercial and industrial designers. (n.d.). Retrieved November 2016, from http://www.bls.gov/oes/current/oes271021.htm Brown, D. (2002). Career choice and development. Retrieved from http://www.borbelytiborbors.extra.hu/ZSKF/CareerDevelopment.pdf Brown , Gordon. “London Design Festival .” London Design Festival. London Design Festival, 2006, London, UK. "Success does not happen by accident, it happens by design." Buchanan, R. (1992). Wicked Problems in Design Thinking. Design Issues,8(2), 5. doi:10.2307/1511637 Europe, Alzheimer. (2009), “The Four Main Approaches.” Retrieved February 08, 2017 Harvey, L. (2000). New realities: The relationship between higher education and employment. Tertiary Education and Management,6(1), 3-17. doi:10.1080/13583883.2000.9967007 Heskett, J. (1980). Industrial design. New York: Thames and Hudson. Hookway, C. (2000). 7 Pragmatism. The Proper Ambition of Science, 2, 103. Hookway, C (Summer 2016 Edition), "Pragmatism", The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), ICSID, (2016). Definition of industrial design. (n.d.). Retrieved from http://www.icsid.org/about/definition/ Industrial Design. (n.d.). Retrieved November, 2016, from http://www.merriamwebster.com/ John , Boyd R. (1995). The Essence of Winning and Losing. 28, June, 1995 Pettinger, T. (2015, September). Causes of unemployment. Retrieved November, 2016, from http://www.economicshelp.org/macroeconomics/unemployment/causes Phifer, P. (2003) College Majors and Careers, Fifth Edition. New York, NY: Ferguson Publication. Robinson, N. K., Meyer, D., Prince, J. P., Mclean, C., & Low, R. (2000). Mining the Internet for Career Information: A Model Approach for College Students. Journal of Career Assessment,8(1), 37-54.
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Ross, S. E., Niebling, B. C., & Heckert, T. M. (2008). Sources of stress among college students. College Student Journal ,33(2), 312-318. Staff, I. (2010, May 15). Hard Skills. Retrieved February, 2017, from http://www.investopedia.com/terms/h/hard-skills.asp What is proficiency? definition and meaning. (n.d.). Retrieved February, 2017, from http://www.businessdictionary.com/definition/proficiency.html What Is Industrial Design? (2016, September 20). Retrieved November, 2016, from http://www.idsa.org/education/what-is-industrial-design Yang, M., You, M., & Chen, F. (2005). Competencies and qualifications for industrial design jobs: Implications for design practice, education, and student career guidance. Design Studies,26(2), 155-189. doi:10.1016/j.destud.2004.09.003 Zane, J. P. (2015, March 19). In the Age of Information, Specializing to Survive. Retrieved November, 2016, from http://www.nytimes.com/2015/03/20/education/in-theage-of-information-specializing-to-survive.html
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Acknowledgements I would like to express my gratitude to the following individuals, without whom this project would not have been possible:
My Thesis Chair, EunSook Kwon, for her support, patience, and countless lessons which inspired me to pursue this education focused project.
My Thesis Committee Members, Dr. Gordon Vos and Professor Mark Kimbrough, for your expertise and his willingness to provide constructive criticism at every step.
All the faculty and students of industrial design department, whose encouragement, creativity, and constant support motivated me to make a successful career guidance system.
My family and friends, for understanding and encouraging my commitment to my studies.
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Vita Mark T. Williams II was born in Houston, TX on the 2nd of November 1990, and is the second child of Mark and Susan Williams. After graduating from George Washington Carver for Applied Technology, Engineering and the Arts in 2008, Mark obtained a Bachelor of Arts in Art History from Baylor University in Waco Texas. While there, he joined Tau Kappa Epsilon in 2009 and in 2012 he enlisted as a Combat Engineer in the United States Army, completing his degree in May of 2013. Mark has worked in customer service, sales, marketing, recruitment and within the food & beverage industry. In 2014 Mark entered the University of Houston to pursue a Master of Science in industrial design while working as a Design & Research Intern at Smith & Company Architects and will be the third graduate of the program. During his time at the University of Houston he was a graduate of both the national and regional cohorts of the National Science Foundation Innovation Corps Program and Captain of the University of Houston’s Rugby team during their first year on the D1A level within the Red River Conference. Her”, which is set to sold in stores, on Amazon, and internationally in the Fall of 2018Mark hopes to pursue a fulfilling career within education and design with a focus on educational systems, educational products, and educational environments.
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Appendix A: Research Materials
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Appendix B: Group Summaries and Data
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Appendix B: Group 1 Summary and data
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Appendix B: Group 2 Summary and data
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Appendix B: Group 3 Summary and data
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