Assessing students' self-assessment ability in an interdisciplinary domain

PurposeThe purpose of this study is to determine whether students' self-assessment (SSA) could be used as a significant attribute to predict students' future academic achievement.Design/methodology/approachThe authors address how well students can assess their abilities and study the relationship between this ability and demographic properties and previous study performance. The authors present the study results by measuring the relationship between the SSA across five different topics and comparing them with the students' performance in these topics using short tests. The test has been voluntarily taken by more than 300 students planning to enroll in the School of Business Informatics and Mathematics master's programs at the University of Mannheim.FindingsThe study results reveal which attributes are mostly associated with the accuracy level of SSA in higher education. The authors conclude that SSA, it can be valuable in predicting master's students' academic achievement when taking specific measures when designing the predictive module.Research limitations/implicationsDue to time constraints, the study was restricted only to students applying to master's programs at the Faculty of Business Informatics and Mathematics at the University of Mannheim. This resulted in collecting a limited data set. Also, the scope of this study was restricted to testing the accuracy of SSA and did not test using it as an attribute for predicting students' academic achievement.Originality/valuePredicting students' academic performance in higher education is beneficial from different perspectives. The literature reveals that a considerable amount of work is published to analyze and predict academic performance in higher education. However, most of the published work relies on attributes such as demographics, teachers' assessment, and examination scores for performing their prediction while neglecting the use of other forms of evaluation such as SSA or self-evaluation.

[1]  Heiner Stuckenschmidt,et al.  Predicting Academic Outcomes: A Survey from 2007 Till 2018 , 2020, Technol. Knowl. Learn..

[2]  Liam Rourke,et al.  Validity in quantitative content analysis , 2004 .

[3]  M. McConnell,et al.  Self-assessment differences between genders in a low-stakes objective structured clinical examination (OSCE) , 2018, BMC Research Notes.

[4]  R. McIntosh,et al.  Wise up: Clarifying the role of metacognition in the Dunning-Kruger effect. , 2019, Journal of experimental psychology. General.

[5]  J. Kruger,et al.  Unskilled and unaware of it: how difficulties in recognizing one's own incompetence lead to inflated self-assessments. , 1999, Journal of personality and social psychology.

[6]  J. Suls,et al.  Flawed Self-Assessment , 2004, Psychological science in the public interest : a journal of the American Psychological Society.

[7]  Andrew Walsh,et al.  Information literacy assessment: Where do we start? , 2009, J. Libr. Inf. Sci..

[8]  Ruth Butler,et al.  Are positive illusions about academic competence always adaptive, under all circumstances: New results and future directions , 2011 .

[9]  Traci Sitzmann,et al.  When is ignorance bliss? The effects of inaccurate self-assessments of knowledge on learning and attrition , 2012 .

[10]  Gavin T. L. Brown,et al.  Accuracy in student self-assessment: directions and cautions for research , 2015 .

[11]  Ulrike Malmendier,et al.  CEO Overconfidence and Corporate Investment , 2002 .

[12]  J. Henrich,et al.  The weirdest people in the world? , 2010, Behavioral and Brain Sciences.

[13]  D. Ruble,et al.  The Development of Achievement-related Expectancies , 2007 .

[14]  Janet Metcalfe,et al.  Overconfidence in children's multi-trial judgments of learning , 2014 .

[15]  Winston R. Sieck,et al.  Organizational Behavior and Human Decision Processes Cross-cultural Variations in Probability Judgment Accuracy: beyond General Knowledge Overconfidence? , 2022 .

[16]  Zi Yan.  Student self-assessment practices: the role of gender, school level and goal orientation , 2016 .

[17]  J. Yates,et al.  General knowledge overconfidence : Cross-national variations, response style, and reality , 1997 .

[18]  Ulrich Schmidt,et al.  Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test , 2016, Front. Psychol..

[19]  N. Feather,et al.  Reactions to male and female success and failure in sex-linked occupations: impressions of personality, causal attributions, and perceived likelihood of different consequences. , 1975, Journal of personality and social psychology.

[20]  J. Eccles,et al.  Age and gender differences in children's self- and task perceptions during elementary school. , 1993, Child development.

[21]  D. Moore,et al.  Overconfidence Across Cultures , 2018 .

[22]  Jude Carroll,et al.  If I was going there I wouldn’t start from here: a critical commentary on current assessment practice , 2011 .

[23]  J. Earl,et al.  Accuracy in Self-Assessment: The Role of Ability, Feedback, Self-Efficacy and Goal Orientation , 2008 .

[24]  Denise A Jackson.  Self-assessment of employability skill outcomes among undergraduates and alignment with academic ratings , 2014 .

[25]  D. Boud,et al.  Quantitative studies of student self-assessment in higher education: a critical analysis of findings , 1989 .

[26]  S. Levinson,et al.  WEIRD languages have misled us, too , 2010, Behavioral and Brain Sciences.

[27]  H. Markus,et al.  Culture and the self: Implications for cognition, emotion, and motivation. , 1991 .

[28]  R. Tejeiro,et al.  Summative self-assessment in higher education: implications of its counting towards the final mark , 2012 .

[29]  V. Klenowski,et al.  Student Self‐evaluation Processes in Student‐centred Teaching and Learning Contexts of Australia and England , 1995 .

[30]  Weiqiang Wang.  Using rubrics in student self-assessment: student perceptions in the English as a foreign language writing context , 2017 .

[31]  L. Siow.  Students' Perceptions on Self- and Peer-Assessment in Enhancing Learning Experience. , 2015 .

[32]  Kathleen D. Vohs,et al.  Illusions of Learning: Irrelevant Emotions Inflate Judgments of Learning , 2015 .

[33]  D. Boud,et al.  Student Self-Assessment in Higher Education: A Meta-Analysis , 1989 .

[34]  R. Edwards,et al.  Medical student self-assessment of performance on an obstetrics and gynecology clerkship. , 2003, American journal of obstetrics and gynecology.

[35]  Socialization of perceived academic competence among highly competent children. , 1987 .

[36]  Domingo Verano-Tacoronte,et al.  Is University Students’ Self-Assessment Accurate? , 2015 .

[37]  M. Bong,et al.  Comparison of Self-Beliefs for Predicting Student Motivation and Achievement , 2012 .

[38]  Linda Leach,et al.  Optional self-assessment: some tensions and dilemmas , 2012 .

[39]  M. Tousignant,et al.  Accuracy of Student Self-Assessment Ability Compared to Their Own Performance in a Problem-Based Learning Medical Program: A Correlation Study , 2002, Advances in health sciences education : theory and practice.

[40]  Sara M. González-Betancor,et al.  Self-assessment accuracy in higher education: The influence of gender and performance of university students , 2019 .

[41]  M. Soltaninejad.  Investigating Predictive Role of 2x2 Achievement Goal Orientations on Learning Strategies with Structural Equation Modeling. , 2015 .

[42]  Dan J. Putka,et al.  Two studies examining the negative effect of self-efficacy on performance. , 2002, The Journal of applied psychology.

[43]  J. Sargeant,et al.  Self‐assessment and continuing professional development: The Canadian perspective , 2008, The Journal of continuing education in the health professions.

[44]  Rachel T. A. Croson,et al.  Gender Differences in Preferences , 2009 .

[45]  Saurabh Pal.  Mining Educational Data Using Classification to Decrease Dropout Rate of Students , 2012, ArXiv.

[46]  Zlatko J. Kovacic,et al.  Early Prediction of Student Success: Mining Students Enrolment Data , 2010 .

[47]  Gavin T. L. Brown,et al.  The Future of Self-Assessment in Classroom Practice: Reframing Self-Assessment as a Core Competency. , 2014 .

[48]  Using Educational Data Mining to Predict Students’ Academic Performance for Applying Early Interventions , 2021, Journal of Information Technology Education: Innovations in Practice.

[49]  Martin Valcke,et al.  How effective are self- and peer assessment of oral presentation skills compared with teachers’ assessments? , 2012 .

[50]  Gavin T. L. Brown,et al.  The Future of Student Self-Assessment: a Review of Known Unknowns and Potential Directions , 2016 .

[51]  Marian M. Larisey,et al.  Student Self-Assessment , 1994 .

[52]  T. Gog,et al.  Effects of training self-assessment and using assessment standards on retrospective and prospective monitoring of problem solving , 2014 .

[53]  H. Sullivan,et al.  Student self-evaluation, teacher evaluation, and learner performance , 2004 .