Do cross-sectional student assessment data make a reasonable proxy for longitudinal data?

Yorke, Mantz; Zaitseva, Elena

doi:10.1080/02602938.2013.769199

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…Within-subjects versus between-subjects data Consistent with findings for academic performance (Yorke and Zaitseva 2013), there was good agreement between samples, which became compelling when more liberal methods of comparison was applied. It appears that BS measures are sufficiently accurate enough to make 'probabilistic' decisions on operational aspects of teaching, assessment and course organisation, which cannot be deferred until evidence meets stringent scientific standards (e.g.…”

Section: Perceptions Of Atmosphere and Teaching/learningsupporting

confidence: 65%

“…Consequently, even stable performance between years one and two could reflect suboptimal student progress (Yorke 2015). Previous research indicated that a second year slump in marks occurred in around one quarter of programmes, without specifying the magnitude (Yorke and Zaitseva 2013).…”

Section: Figure 1 Tinto's (2015) Model Of Student Motivation and Permentioning

confidence: 99%

“…In contrast, BS comparisons can be made swiftly, such that suboptimal trends might be addressed in time to benefit the study population. Yorke and Zaitseva (2013) compared the utility of WS and BS approaches for assessing trends in academic performance between years. BS approaches matched 'true' WS data in around 70% of cases.…”

Section: Figure 1 Tinto's (2015) Model Of Student Motivation and Permentioning

confidence: 99%

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Deciphering the sophomore slump: changes to student perceptions during the undergraduate journey

Webb

Cotton

2018

High Educ

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The second year of university is little-researched, despite being a focal point for declining performance, persistence and satisfaction. It is important to establish appropriate methods for studying this 'sophomore slump' and to pinpoint specific antecedents from broad domains noted in literature (e.g. students' social integration, perceptions of the curriculum). Using a novel methodology, 166 undergraduates were surveyed in successive years of study to derive a gold standard 'within-subjects' data sample. Under a replicated design, a 'between-subjects' sample of over 1000 students completed the same e-survey just once, in year one, two or three. Quantitative comparison of the responses across years showed over 85% agreement between samples. This endorses between-subject approaches (i.e. simultaneously surveying students from different years) to facilitate rapid interventions that benefit students before they graduate. In terms of detailed findings, year two saw positive trends in students' academic engagement (e.g. selfreported independent study time), social integration (e.g. feeling accepted, involvement in extra-curricular activities), and views on teaching staff (e.g. approachability). Although appraisals remained broadly favourable there was, in contrast, significant deterioration in global perceptions of the learning atmosphere (e.g. course enjoyment), as well as specific elements of the teaching provision (e.g. contact hours, feedback). Notably, there appeared to be little progression in students' academic self-perceptions (e.g. confidence to make presentations, enter class debates). Year two also saw increased thoughts of drop-out. These results highlight the unique character of the second year at university and indicate potential target areas for enhancing this phase of the undergraduate journey.

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Section: Perceptions Of Atmosphere and Teaching/learningsupporting

confidence: 65%

Section: Figure 1 Tinto's (2015) Model Of Student Motivation and Permentioning

confidence: 99%

Section: Figure 1 Tinto's (2015) Model Of Student Motivation and Permentioning

confidence: 99%

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Deciphering the sophomore slump: changes to student perceptions during the undergraduate journey

Webb

Cotton

2018

High Educ

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“…Of the three TEF criteria, assessing and comparing student progression and retention is the most difficult to measure of the three and is of most interest in terms of student engagement in learning. Yorke ( 2013 ) describes the complexities of capturing what he considers to be reliable student assessment data over extended periods of time, and emphasises the importance of understanding the nature of different programmes and modes of study. Even when contextual knowledge and data are available, quality is a contested concept.…”

Section: Progression Retention and Ideas Of Engagementmentioning

confidence: 99%

Higher Education’s Panopticon? Learning Analytics, Ethics and Student Engagement

Wintrup

2017

High Educ Policy

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Is learning analytics a movement that seeks to rebalance the effects of higher education's apparent blindness to privilege, its unequal access regimes and persistent retention and attainment gaps through a more skilful and strategic use of student data? Or is it part of a larger project to surveil students and staff in higher education, in pursuit of greater efficiency and control? Both perspectives are alive and well in debates surrounding higher education's changing relationship with its students. The systematic institutional use of student-generated data known as learning analytics is raising practical, methodological and ethical questions, which are yet to be answered. However, a proposed framework for assessing and comparing the quality of learning and teaching in the UK is poised to use such data as one of its metrics. Learning analytics and its relationship to student engagement is explored through the first known research to utilise an adaptation of Kuh's National Survey of Student Engagement with people studying Massive Open Online Courses. Contrasting perspectives are offered by Siemen's theory of connectivist learning and Foucault's notion of the panopticon. If the potential of analytics is to be realised in terms of meaningful quality improvement, questions remain concerning ethics, trust, its role in engagement in learning, and the ways in which policy might effectively safeguard the longer-term individual and collective interests of students.Keywords 1,* 1 e.Proofing

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“…It is important to note this type of longitudinal approach is not without its critics within the field of assessment and evaluation (Yorke and Zaitseva 2013). Astin (2012) argues measurement tools similar to ours are not informative because there are too many confounding factors to determine causality.…”

Section: Analysis Of Lab Reportsmentioning

confidence: 99%

Untitled

2017

stem

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Full version of volume 1 of the Proceedings of the Interdisciplinary STEM Teaching and Learning Conference.This complete issue is available in Proceedings of the Interdisciplinary STEM Teaching and Learning Conference:https://digitalcommons.georgiasouthern.edu/stem_proceedings/vol1/iss1/1Editor's NoteIt was with great pleasure that I was able to organize and put together the inaugural volume of the Proceedings of the Interdisciplinary STEM Teaching and Learning Conference. The opportunity to read the different studies and converse with authors from all over the region was rewarding and makes me proud of the good work being done in interdisciplinary STEM education.The first volume of the Proceedings of the Interdisciplinary STEM Teaching and Learning Conference includes topics from special education, curricular integration, using primary resources, methods for using new technologies, and cellular testing. I was truly impressed with the scope of the work presented at the conference and articulated in these papers.I want to acknowledge the Institute for Interdisciplinary STEM at Georgia Southern University and our fellows and affiliates who graciously and quickly assisted with the review process. Thank you to Lisa Stueve for leading this year's conference and Marsha Pate, Kania Greer, and Robert Mayes for all their support along the way. (National Science Foundation, 2015). The underrepresentation is a problem because the nation's competitiveness depends on diverse individuals with STEM knowledge, skills, and abilities to drive innovation that will need to new products and economic growth (Businesshigher Education Forum/A Policy Brief, 2014; National Academies of Sciences, Engineering, and Medicine, 2016; National Science Board, 2016). The author discusses the importance of engaging students with disabilities in informal Science, Technology, Engineering, and Mathematics activities.Keywords: extracurricular, clubs, STEM, disabilities, social skills, soft skills, informal, self-efficacy, self-determination The Importance of Extracurricular Activities for Students with DisabilitiesAll students, including students with disabilities (SWD) who participated in after-school programs that offer a variety of experiences develop skills and self-confidence (Kleinert, Miracle and Sheppard-Jones, 2007). These social and emotional skills are difficult to achieve in the typical classroom setting (Snellman, Silva, Frederick & Putnam, 2015). Kleinert and colleagues (2007) pointed out the Individuals with Disabilities Education Act (IDEA) requires schools to provide access to extracurricular activities and recommended participation in after-school programs is included in students' Individual Education Programs (IEPs). After-school clubs can integrate needed work place (soft skills, i.e. collaboration) and social skills interventions with students who share similar interests in a natural, informal, learning environment. Students with disabilities develop social competence by experiencing friendships and gaining valuable...

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Do cross-sectional student assessment data make a reasonable proxy for longitudinal data?

Cited by 4 publications

References 7 publications

Deciphering the sophomore slump: changes to student perceptions during the undergraduate journey

Deciphering the sophomore slump: changes to student perceptions during the undergraduate journey

Higher Education’s Panopticon? Learning Analytics, Ethics and Student Engagement

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