Elsevier

Computers & Education

Volume 72, March 2014, Pages 100-109
Computers & Education

Online self-assessment and students' success in higher education institutions

https://doi.org/10.1016/j.compedu.2013.10.018Get rights and content

Highlights

  • Students' results from three different generations were compared.

  • Inspecting effects of online self-assessment tests on students' success.

  • Simulation model of course pass rates in higher education institution.

Abstract

This paper validates effects of online self-assessment tests as a formative assessment strategy in one of the first year undergraduate courses. Achieved students' results such as test scores and pass rates are compared for three different generations for the same course but also judged against the exam results of other courses taught in the same semester. The analysis points out that there is a statistically significant difference between the groups for half-semester tests and exam pass rates after online self-assessment tests were introduced. Positive effects on students' success are approximated for the overall institution using a simulation model. Results point out that a small increase in pass rates could significantly impact the overall success i.e. decrease of dropout rates.

Introduction

The selection of assessment techniques and appropriate assessment tools is an integral part of planning the e-learning processes. Most modern Learning Management Systems (LMS) and Virtual Learning Environments (VLE) incorporate functionalities for developing and processing online tests. It is customary to use such system functions for self-assessment purposes and other types of evaluation in both full distance learning and hybrid learning courses. The use of computer-supported online assessment has been increasing in both summative and formative assessment areas (Bull and Dalziel, 2003, Bälter et al., 2013).

Interacting online requires educators to rethink online pedagogy so as to support meaningful (higher-order) learning and its assessment (Gikandi, Morrow, & Davis, 2011). The development of an assessment strategy should take into account the purpose of the evaluation results plus it should always be planned simultaneously with the preparation of learning activities. During the process, assessment can be perceived as one of the enablers of innovation and change in an educational setting. Sometimes, this can be a tough challenge in the context of compulsory education where the norm is even now the traditional assessment that is to say summative and teacher centered assessment (Granić, Mifsud, & Ćukušić, 2009). Growing in popularity, formative assessment is to a greater extent promoted as “a moment of learning” – it allows beneficial comparisons between the actual and referral levels of achievement and so the results can be used to identify gaps between the compared levels (Black & Wiliam, 1998). E-learning scenarios should therefore aim to maximize the potential of an LMS to implement a series of formative assessment strategies (i.e. assessments “for” learning).

It is not essential or even possible to integrate online assessment activities into every lesson since this process requires a significant amount of time and creativity in order to create good series of questions (Mödritscher, 2006) with respect to: the lesson topic; learning outcomes; the type of questions; number of participants; cheating prevention mechanisms; the time for assessment etc. Nevertheless, there are tests that may be incorporated as a part of almost any learning scenario such as quizzes at the beginning of the lesson (in terms of pointing out the gaps in foreknowledge of a group), during the lesson (measuring progress in understanding) or the end of the lesson (to assist the recap). In that respect, an important assessment strategy is self-assessment.

The study presented hereinafter deals with effects of online self-assessment in one university course of hybrid type and discusses the potential extrapolation of the identified result to the whole system, to be exact higher education institution (HEI) by simulation method. Simulation modeling can support managerial approach (Greasley, 2003) to change key educational processes in order to understand and measure variations in performance indicators such as student success. An important characteristic of the method is the possibility of repeating the simulation runs with changing input parameters (i.e. increased course pass rates as a result of introducing self-assessment tests) and monitoring the impact of changes in outputs (overall HEI success in terms of number of students completing the study programs).

After presenting the theoretical and empirical background of the study in the second part of the paper, results of quantitative and comparative study are presented in the third part. Fourth part illustrates and discuses the potential impact of online self-assessments to the whole institution and the overall educational process outcomes. The final, fifth part of the paper concludes the study summarizing the results.

Section snippets

Effectiveness of online (self-) assessment tools

Self-assessment can result in major benefits both for teachers and students (McConnell, 2006), specifically it is more oriented to students, reduces some of the teachers' load, provides instant feedback and helps to remove certain “barriers” between teachers and students. Furthermore, the students become less dependent on their teachers, responsible and autonomous; they take on a more proactive role and develop self-confidence, while the teachers can evaluate the effects of their teaching

Research methodology

The overall aim of the research was to design, implement and monitor the changes in the teaching process in the first-year undergraduate course Information Technology at Faculty of Economics, University of Split. Significant improvement of the exam results and test scores was expected after introduction of online self-assessment tests.

Examining student- and course-level indicators

Table 1 shows the mean and the deviation of students' results for self-assessment test, half-semester tests and the exams in academic year 2009/2010 and 2010/2011. The maximum number of points per self-assessment test was 10 (2009/2010) and 20 (2010/2011) with students achieving on average 25.46 (63.65%) and 49.02 (61.27%) respectively in the first four self-assessment tests, and much less 21.01 (52.53%) and 37.56 (46.96%) respectively in other four test. Overall, the students' average scores

Conclusion

Achieved students' results from a first year undergraduate course were compared for three different generations. After the implementation of online self-assessment tests in 2009/2010, the correlation between the exam results and the number of points in self-assessment tests was detected. By the end of the second year the self-assessment tests were used, the real and significant correlation between the points achieved in self-assessment tests and the number of points achieved in both

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