Editorial: TEN STARS Special Issue

This special issue was produced by the TEN-STARS network, an international network of tertiary staff, students, graduates and employers dedicated to furthering research and practice related to graduate employability. The Employability Network, was formed at the 2018 STARS conference (www.unistars.org) in response to shared interests that are very much aligned to those of the Journal of Learning and Teaching for Graduate Employability. It is therefore with great pleasure that we introduce the Journal’s first special issue, which is also the network’s first collaborative output. The first issue of the Journal of Teaching and Learning for Graduate Employability was published in 2010, ‘as a forum for fostering interdisciplinary dialogue among researchers, teacher scholars, careers staff and industry and professional practitioners concerned about graduate employability’ (Quin, 2010). Almost ten years on, dialogue among those key stakeholders is no less important, and assuring graduate employability remains a challenge that spans international contexts. In fact, with growing global uncertainty related to rapid technological developments and the changing world of work, alongside other equally concerning social and political disruptions, the preparation of graduates to face uncertainty in and beyond the workforce is arguably more important than ever (Oliver & Jorre de St Jorre, 2018). Fortunately, thanks to the dedication of many, and platforms such as this Journal, there is now an expansive and growing body of research and evidence based practice that can be drawn upon - to design, question, and redesign - teaching and learning for graduate employability. Universities and academics are often at the centre of discourse about graduate employability, but in reality, concerns and responsibilities are shared more broadly amongst: leaders of tertiary institutions (university and non-university providers); academics in and beyond traditional faculty roles; and other staff who contribute to the student experience and graduate outcomes through diverse roles (such as those that contribute to career learning services, learning design, and student support, to name just a few). Students, graduates, employers and professional associations, as well as government and quality assurance agencies, are also key stakeholders, whose influence and perspectives are essential to developing effective strategies (Kinash, Crane, Judd, & Knight, 2015; Kinash, et al., 2015). With this in mind, the TEN-STARS network was convened by Professor Shelley Kinash, to encourage and support collaboration between all those interested in continuing to discuss, inform, and influence graduate employability. This special issue, was conceived as a way of sharing some of the network’s diverse and collective expertise with a broader audience, who are also invited to become part of our network (https://tenstars.graduateemployability.com/). All of the papers in this TEN STARS Special Issue are empirical, theoretically grounded and richly informed by the growing body of published employability literature. The roles and experience of our contributing authors are diverse, as are their research questions, methods and methodologies. However, all of the inquiries shared have been designed to impact graduate employability, so they are all contextualised to tertiary education, and provide recommendations for further research and efficacious practice related to learning and teaching for employability. Importantly, none of the approaches examined are bolt-ons (requiring already busy students to do more). Rather, authors have focussed on deeply considered approaches to designing and refining the tertiary educational experience, so that employability and careers perspectives are embedded in the student learning experience, and deeply contextualised to disciplines

Assessment for inclusion: rethinking contemporary strategies in assessment design

Assessment has multiple purposes, one of which is to judge if students have met outcomes at the requisite level. Underperformance in assessment is frequently positioned as a problem of the student and attributed to student diversity and/or background characteristics. However, the assessment might also be inequitable and therefore exclude students inappropriately. To be inclusive, assessment design needs to be reconsidered, and educators should look beyond simplistic categories of disability or social equity groups, towards considering and accounting for diversity on many spectra. This article introduces the concept of assessment for inclusion, which seeks to ensure diverse students are not disadvantaged through assessment practices. Assumptions in assessment design are problematised from this point of view, and three central concerns relating to assessment traditions, assessment expectations, and academic integrity are interrogated. Contemporary design strategies of authentic assessment, programmatic assessment, and assessment for distinctiveness are then harnessed to illustrate approaches to assessment for inclusion. Assessment for inclusion therefore builds on the synergies between inclusive practice and good assessment design

Research into the diversification of university careers in learning and teaching and intentionally closing-the-loop on graduate employability

Universities are both a source of employable graduates and careers. This paper examines universities as developers and employers of their own graduates from the perspective of employees and recruited positions. Research questions were: what do learning and teaching careers look like at universities, and; what are the occupational patterns, satisfactions and concerns of the staff in those careers? An autoethnographic account of employees’ career journeys (all of whom were employed in learning and teaching or closely related areas) from five different universities were shared, compared and contrasted. Two of these universities are profiled as having a large proportion of students from target equity groups and therefore have intentionally recruited learning and teaching staff to widen student participation. A desktop review of six months of university employment vacancies from these two universities was conducted. A consistent theme across the autoethnographic stories was a feeling of being an outsider. The authors’ hypothesis is that this is related to haphazard preparation for learning and teaching positions. Of the 322 university vacancies, 84% were for professional staff, 23% of which were in learning and teaching, with the most prevalent role being Coordinator. Fourteen per cent were for academic staff, 64% of which involved learning and teaching, and the most prevalent title was Lecturer/Senior Lecturer. Key takeaways include recommendations for universities to intentionally enhance the employability of graduates who pursue learning and teaching positions within universities, and for prospective university learning and teaching staff to enhance their employability

The age-dependent influence of self-reported health and job characteristics on retirement

OBJECTIVES: Social scientists and economists doubt the usefulness of self-reported health status as an indicator of overall health status. Self-reported health acts as a justification for retirement when this decision is in reality driven by other reasons. In this study, we looked at income, job satisfaction, and job status. METHODS: We introduce a survival model (Cox model) that simultaneously includes both health and job characteristics as independent variables. We also take the age-dependent character of these effects into account. RESULTS: An analysis of the European Community Household Panel data did not validate the justification bias with respect to these variables. The addition of job characteristics had no influence on the effect estimates of self-reported health. CONCLUSIONS: We found significant effects for self-reported health as well as for objective health measures. The addition of job characteristics did not contribute to the explanation of the effect of self-reported health falsifying the justification bias hypothesis

Delving into Institutional Diversity Messaging A Cross-Institutional Analysis of Student and Faculty Interpretations of Undergraduate Experiences of Equity, Diversity, and Inclusion in University Websites

Recognizing that university statements about equity, diversity, and inclusion are often cosmetic, performative, or at best, aspirational, rather than indicative of on-campus realities, this project analyzes interpretations of student identity and diversity through publicly available materials. The primary purpose of this research was to investigate how university messages about equity, diversity, and inclusion, available through public websites, are interpreted by faculty and students. Using a students-as-partners approach, we identified and analyzed themes based on our own perceptions and understandings of each of five university websites University of Calgary (Canada), University of Alabama (USA), Deakin University (Australia), University of Exeter (UK), and Portland State University (USA). While equity, diversity, and inclusion are signature initiatives at many universities, we found that analyses of their websites suggest that the ways in which those are operationalized differ. The patterns identified suggest that messaging through university websites can promote or detract from equity, diversity, and inclusion in university settings, and we observed differences in the ways in which institutions operationalized and represented initiatives related to equity, diversity, and inclusion. Exploring how these efforts at our five institutions are messaged to and interpreted by students provides a better understanding of the institutional priorities and the assumed values identified by student co-researchers. The use of student co-researchers proved an especially valuable contribution to this analysis to gain perspectives about presentations of student identity and diversity. Using this form of embedded research, we identify the limited presentations of and perceptions around diversity at institutions of higher education cited by student co-researchers

Digital disruption meets the academic timetable: start learning anytime

Many universities claim to provide flexible learning opportunities, but most still require students to keep pace with prescribed curriculum delivery and assessment deadlines, and few have disrupted the academiccalendar. In this paper, we report on an innovation called ‘Start anytime’ that was purposefully designed to break from a trimester model and instead give students the flexibility to study in their own space andpace online. Here we report on measures put in place to support students during self-paced online study, and share insights from research investigating students’ expectations and experience of ‘Start anytime’.For many students, the self-management required for self-paced study was a challenge, but for most students those challenges were out weighted by the benefits of flexible learning. Importantly, the majorityof students thought that access to learning support and teaching staff was the same or better in ‘Start anytime’ units than in a timetabled unit, and many students found that self-paced study was easier andmore enjoyable. Thus, we have shown that where it is carefully designed and supported, self-paced online learning and disruption of the academic calendar, can have considerable benefits for experienced adult learners who have difficulty fitting study around their busy lives

Assessing the use of mode preference as a covariate for the estimation of measurement effects between modes: a sequential mixed mode experiment

"Mixed mode surveys are presented as a solution to increasing survey costs and decreasing response rates. The disadvantage of such designs is the lack of control over mode effects and the interaction between selection and measurement effects. In a mixed mode survey, measurement effects can put into doubt data comparability between subgroups, or similarly between waves or rounds of a survey conducted using different modes. To understand the extent of measurement effects, selection and measurement effects between modes have to be disentangled. Almost all techniques to separate these effects depend on covariates that are assumed to be mode-insensitive and to fully explain selection effects. Most of the time, these covariates are sociodemographic variables that might be mode-insensitive, but fail to sufficiently explain selection effects. The aim of this research is to assess the performance of mode preference variables as covariates to evaluate selection and measurement effects between modes. In 2012, a mixed mode survey - a web questionnaire followed by face-to-face interviews - was conducted alongside the face-to-face European Social Survey in Estonia (Ainsaar et al., 2013). The questionnaire included mode preference items. In this paper, the effects of the trade-offs between the two assumptions on the precision of estimated selection and measurement effects are compared. The results show that while adding the mode preference to the propensity score model seems to increase the explanatory power of web participation, it decreases the correlation between propensity scores and target variables. In addition, the estimated selection and measurement effects do not always fit the expectation that more selection effects are explained and more measurement effects are detected." (author's abstract

Evaluating Mode Effects in Mixed-Mode Survey Data Using Covariate Adjustment Models

Abstract The confounding of selection and measurement effects between different modes is a disadvantage of mixed-mode surveys. Solutions to this problem have been suggested in several studies. Most use adjusting covariates to control selection effects. Unfortunately, these covariates must meet strong assumptions, which are generally ignored. This article discusses these assumptions in greater detail and also provides an alternative model for solving the problem. This alternative uses adjusting covariates, explaining measurement effects instead of selection effects. The application of both models is illustrated by using data from a survey on opinions about surveys, which yields mode effects in line with expectations for the latter model, and mode effects contrary to expectations for the former model. However, the validity of these results depends entirely on the (ad hoc) covariates chosen. Research into better covariates might thus be a topic for future studies.</jats:p