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Optimising Moodle quizzes for online assessments
Open accessAbstract
Computer-aided learning management systems (LMSs) are widely used in higher education and are viewed as beneficial when transitioning from conventional face-to-face teaching to fully online courses. While LMSs have unique tools for transferring and assessing knowledge, their ability to engage and assess learners needs further investigation. This paper focuses on a study examining the LMS “Moodle” to ascertain the effectiveness of “Moodle quizzes” to improve, assess and distinguish knowledge in a civil engineering course at an Australian university. The course has a database comprising 62 formative and 61 summative quiz questions with embedded text, images, audio and video. This study investigates the use of these quiz questions with four course cohorts and 169 students. The quizzes assessed competencies of students during various stages of a study period through automated marking. The suitability of questions to assess and distinguish student knowledge levels was determined using a psychometric analysis based on facility index (FI) and the discrimination index (DI) statistics embedded within the Moodle quizzes. This study highlights strategies used to set and review quiz questions for formative and summative assessments. Results indicated that students were engaged and satisfied in the formative assessment because they viewed the interactive videos between 2 and 6 times and 65% of students attempted all the formative questions. The FI indicated student pass rate for the summative questions and DI indicated the difficulty of these questions, while the combination of FI and DI results separated students with different knowledge levels. Using these Moodle statistics provided information to make effective decisions on how to improve the summative quizzes. The multimodal quizzes were effective in teaching and assessing a theoretical engineering course and provided efficient methods to replace conventional assessments. The FI and DI indexes are useful statistical tools in redesigning appropriate sets of questions. Time-poor academics will benefit from using these easily attainable Moodle statistics to inform decisions while revising the quizzes and making assessments more autonomous.
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“Some studies which focused on the assessment process investigated the usefulness of the online environment for instructors to organise assessments, the usefulness of giving responsibilities to students during assessment (mainly via peer assessments), and using Moodle statistics and analytics to evaluate and improve the quality assessment process (Cakiroglu et al., 2017; Gamage et al., 2019;”
From A systematic review on trends in using Moodle for teaching and learning (2022) · cites this paper as Gamage et al., 2019
In the citing paper
“Ten percent of the articles reviewed discussed the in-built statistical tools such as the facility index and discrimination index along with the databases available in LMSs for the use of educational and research purposes (Fenu et al., 2017; Gamage et al., 2019; Monllaó Olivé et al., 2020).”
From A systematic review on trends in using Moodle for teaching and learning (2022) · cites this paper as Gamage et al., 2019
Citations
Cites
Ennis, R. H. (1993) · Theory Into Practice · doi:10.1080/00405849309543594 · Cited by 1,101
Philipsen, B., Tondeur, J., Pareja Roblin, N., Vanslambrouck, S., & Zhu, C. (2019) · Educational Technology Research and Development · doi:10.1007/s11423-019-09645-8 · Cited by 391
Huang, S., & Fang, N. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.08.015 · Cited by 374
Profiles in self-regulated learning and their correlates for online and blended learning students
Broadbent, J., & Fuller‐Tyszkiewicz, M. (2018) · Educational Technology Research and Development · doi:10.1007/s11423-018-9595-9 · Cited by 165
Engaging with blended learning to improve students’ learning outcomes
Francis, R. L., & Shannon, S. J. (2013) · European Journal of Engineering Education · doi:10.1080/03043797.2013.766679 · Cited by 124
Tertiary student attitudes to invigilated, online summative examinations
James, R. (2016) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-016-0015-0 · Cited by 120
West, J., & Turner, W. (2015) · Innovations in Education and Teaching International · doi:10.1080/14703297.2014.1003954 · Cited by 116
Active learning through online quizzes: better learning and less (busy) work
Cook, B. R., & Babon, A. (2016) · Journal of Geography in Higher Education · doi:10.1080/03098265.2016.1185772 · Cited by 93
ONLINE QUIZZES IN A VIRTUAL LEARNING ENVIRONMENT AS A TOOL FOR FORMATIVE ASSESSMENT
Cohen, D., & Sasson, I. (2016) · RACO (Revistes Catalanes amb Accés Obert) (Consorci de Serveis Universitaris de Catalunya) · doi:10.3926/jotse.217 · Cited by 72
Thévenot, C., Devidal, M., Barrouillet, P., & Fayol, M. (2006) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470210600587927 · Cited by 68
Sullivan, D. P. (2016) · Online Learning · doi:10.24059/olj.v20i3.650 · Cited by 67
Arithmetic word problem solving: Evidence for the construction of a mental model
Thévenot, C. (2009) · Acta Psychologica · doi:10.1016/j.actpsy.2009.10.004 · Cited by 66
Predicting college success: the importance of ability and non-cognitive variables
Ransdell, S. (2001) · International Journal of Educational Research · doi:10.1016/s0883-0355(01)00032-5 · Cited by 62
Ting, S. R. (2001) · International journal of engineering education · Cited by 54
A systematic review of stakeholder views of selection methods for medical schools admission
Kelly, M. E., Patterson, F., O’Flynn, S., Mulligan, J., & Murphy, A. W. (2018) · BMC Medical Education · doi:10.1186/s12909-018-1235-x · Cited by 52
OPEN SOURCE LEARNING MANAGEMENT SYSTEMS IN DISTANCE LEARNING
Aydın, C. Ç., & Tirkeş, G. (2010) · Cited by 45
Immediate detailed feedback to test-enhanced learning: An effective online educational tool
Wojcikowski, K., & Kirk, L. (2013) · Medical Teacher · doi:10.3109/0142159x.2013.826793 · Cited by 41
Krause, C. C., Krause, R. F., Krause, R., Gómez, N. R., Jafry, Z. M., & Dinh, V. A. (2017) · Journal of surgical education · doi:10.1016/j.jsurg.2017.03.007 · Cited by 38
Open‐source learning management systems: a predictive model for higher education
van Rooij, S. W. (2011) · Journal of Computer Assisted Learning · doi:10.1111/j.1365-2729.2011.00422.x · Cited by 36
Rinaldi, V. D., Lorr, N. A., & Williams, K. M. (2016) · Anatomical Sciences Education · doi:10.1002/ase.1667 · Cited by 34
Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts
Geary, D. C. (2017) · Cited by 30
Wallihan, R. G., Smith, K. G., Hormann, M. D., Donthi, R. R., Boland, K. A., & Mahan, J. D. (2018) · BMC Medical Education · doi:10.1186/s12909-018-1366-0 · Cited by 25
The Impact of Computer Augmented Online Learning and Assessment Tool
Heo, M., & Chow, A. W. (2005) · Cited by 24
Contemporary Complex Systems and Their Dependability
(2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-91446-6 · Cited by 23
Vicente, S., Orrantia, J., & Verschaffel, L. (2008) · Journal for the Study of Education and Development Infancia y Aprendizaje · doi:10.1174/021037008786140959 · Cited by 22
Kustritz, M. V. R. (2014) · Journal of Veterinary Medical Education · doi:10.3138/jvme.0813-112r1 · Cited by 21
Calibrating Questionnaires by Psychometric Analysis to Evaluate Knowledge
Gómez-Soberón, J. M., Gómez-Soberón, M. C., Higuera, R. C., Arredondo-Rea, S. P., Almaral-Sánchez, J. L., & Covarrubias, F. G. C. (2013) · SAGE Open · doi:10.1177/2158244013499159 · Cited by 19
Exploring the effectiveness of continuous activity with automatic feedback in online calculus
Vinuesa, T. S., Masià, R., Alpiste, M. F. I., & Castells, N. M. (2017) · Computer Applications in Engineering Education · doi:10.1002/cae.21861 · Cited by 19
Weekly online quizzes to a mathematics course for engineering students
Martins, S. G. (2016) · Teaching Mathematics and its Applications An International Journal of the IMA · doi:10.1093/teamat/hrw011 · Cited by 17
Student perceptions of immediate feedback testing in student centered chemistry classes
Schneider, J. L., Ruder, S. M., & Bauer, C. F. (2018) · Chemistry Education Research and Practice · doi:10.1039/c7rp00183e · Cited by 17
Jaeger, M., & Adair, D. (2016) · European Journal of Engineering Education · doi:10.1080/03043797.2016.1153042 · Cited by 16
New era and challenges for a consolidated journal in educational technology in higher education
Duart, J. M., & James, R. (2016) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-016-0001-6 · Cited by 11
Moodle quizzes for assessing statistical topics in engineering studies
Abellán, M. B., & Gisbert, M. G. (2010) · Cited by 10
Initial recommendations of MOOCs characteristics for academic discipline clusters
Salamon, H. M., Ali, N. M., Miskon, S., & Ahmad, N. (2016) · Journal of Theoretical and Applied Information Technology · Cited by 6
A Trustworthy and Privacy Preserving Model for Online Competence Evaluation System
Liagkou, V., & Stylios, C. D. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-91446-6_32 · Cited by 5
Benefits of Active Learning Embedded in Online Content Material Supporting a Flipped Classroom
Maarek, J. I. (2020) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--29845 · Cited by 5
Higher Education Faculty Utilization of Online Technological Tools: A Multilevel Analysis
Jackson, B. (2017) · Journal of educational multimedia and hypermedia · Cited by 4
Fales‐Williams, A. J., Kramer, T., Heer, R., & Danielson, J. A. (2005) · Journal of Veterinary Medical Education · doi:10.3138/jvme.32.1.144 · Cited by 4
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A systematic review on trends in using Moodle for teaching and learning
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Heil, J., & Ifenthaler, D. (2023) · Online Learning · doi:10.24059/olj.v27i1.3398 · Cited by 168
Deák, C., Kumar, B., Szabó, I., Nagy, G., & Szentesi, S. (2021) · Education Sciences · doi:10.3390/educsci11070319 · Cited by 81
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Biancini, G., Ferrato, A., & Limongelli, C. (2024) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3631700.3665233 · Cited by 52
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Al-Maqbali, A., & Hussain, R. M. R. (2022) · Journal of University Teaching and Learning Practice · doi:10.53761/1.19.2.6 · Cited by 42
Metadata
- Authors
- Gamage, S. H. P. W., Ayres, J. R., Behrend, M. B., & Smith, E. J.
- Affiliations
- University of South Australia (AU)
- Corresponding author
- Gamage, Sithara H. P. W.
- Venue
- International Journal of STEM Education
- Published
- 2019-08-13
- Volume
- 6
- Issue
- 1
- ISSN
- 2196-7822 (ISSN-L)
- OpenAlex
- W2967444271
- Cited by
- 128
- References
- 38
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 21 · 2023: 31 · 2022: 30 · 2021: 21 · 2020: 12 · 2019: 1
- FWCI
- 19.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of STEM Education (publishedVersion, cc-by)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- Moodle quizzes, online assessment, virtual learning environments, automated marking, discrimination index, psychometric assessment, formative assessment, summative assessment, student engagement, civil engineering education
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