Scholarship of Teaching and Learning (SoTL)
The SoTL generally refers to the process of generating meaningful knowledge, about an educational discipline, by validating claims through critical reflection (Boyer, 1990, 2015). It aims to enhance the “professional status of tertiary teaching” (Haigh, 2010, p. 1) by making transparent the means by which student learning has been enabled (Trigwell, Martin, Benjamin, & Prosser, 2000).
SoTL as scholarship needs to involve rigorous scholarly inquiry into student learning and thus into teaching as a key aspect of academic practice; that this needs to be made public; and that this process of making it public needs to be subject to peer review.
The Institute for Research in Open and Innovative Education (IROPINE) at the School of Open Learning of Hong Kong Metropolitan University supports HKMU staff for the pursuit of Scholarship of Teaching and Learning (SoTL) through promoting impactful research to advance teaching pedagogies and improve student learning. The Teaching and Learning Research Fund is one of the initiatives to nurture and support teaching and learning research in the University for the enhancement of the quality of our education provision.
The Teaching and Learning Research Fund aims to nurture and support teaching and learning research in the University. The Fund promotes the pursuit of Scholarship of Teaching and Learning (SoTL) in the University and the enhancement of the quality of our teaching and learning through relevant research. The application form and guidance notes for this Teaching and Learning Research Fund can be downloaded through the following links:
Liong M., Yeung D.Y., Cheng G.H.-L., Cheung R.Y.H. (2023). Profiles of ICT identity and their associations with female high school students' intention to study and work in ICT: A mixed-methods approach. Computers and Education, 2023, v.195, 104722. DOI:https://doi.org/10.1016/j.compedu.2022.104722
Yeung M.Y.-L., Cheng H.H.-M., Chan P.T.-W., Kwok D.W.-Y. (2023).Communication Technology and Teacher–Student Relationship in the Tertiary ESL Classroom During the Pandemic: A Case Study.SN Computer Science, v.4 n.2, 202. DOI:https://doi.org/10.1007/s42979-023-01667-7
Ng W.S., Yu G. (2023). The Impacts of Dialogic Interaction to Engage Students in Peer Assessment. Asia-Pacific Education Researcher, v.32 n.1. p.53-64. DOI:https://doi.org/10.1007/s40299-021-00633-2
Fingrut A., Ng H.K.Y. (2023). Studio-based architecture pedagogies in the new normal. International Journal of Mobile Learning and Organisation. v.17, p.117-130. DOI:https://doi.org/10.1504/ijmlo.2023.128353
Chan V. (2023). Investigating the impact of a virtual reality mobile application on learners’ interpreting competence. Journal of Computer Assisted Learning. DOI:https://doi.org/10.1111/jcal.12796
Chung E., Crosthwaite P.R., Lee C. (2023). The use of metadiscourse by secondary-level Chinese learners of English in examination scripts: insights from a corpus-based study. International Review of Applied Linguistics in Language Teaching. DOI:https://doi.org/10.1515/iral-2022-0155
Chan K.K.Y., Bond T., Yan Z. (2023). Application of an Automated Essay Scoring engine to English writing assessment using Many-Facet Rasch Measurement. Language Testing, v.40 n.1, p.61-85. DOI:https://doi.org/10.1177/02655322221076025
Li Z., Li Q., Han J., Zhang Z. (2022). Perspectives of Hybrid Performing Arts Education in the Post-Pandemic Era: An Empirical Study in Hong Kong. Sustainability, v.14 n.15 9194. DOI:https://doi.org/10.3390/su14159194
Lee C. (2022).Revealing Interactions Between Adolescent English Learners and a Computer-Assisted Writing System from the Activity Theory Lens: Two Case Studies.English Language Education, v. 27, p.123-144. DOI:https://doi.org/10.1007/978-3-030-99622-2_9
Lui A.K.-F., Ng S.-C., Cheung S.W.-N. (2022). An Interactive Short Answer Grading System Based on Active Learning Models. 2022 4th International Conference on Computer Science and Technologies in Education, CSTE 2022, p.314-321. DOI: https://doi.org/10.1109/CSTE55932.2022.00065
Chan V. (2022). Using a virtual reality mobile application for interpreting learning: listening to the students' voice. Interactive Learning Environments. DOI:https://doi.org/10.1080/10494820.2022.2147958
Qiu X. (2022).Revisiting the Cognition Hypothesis: the impact of task complexity on L2 learner engagement in task performance in computer-mediated and face-to-face communication. Computer Assisted Language Learning. DOI:https://doi.org/10.1080/09588221.2022.2142245
Li K.C., Wong B.T.-M. (2022). Personalisation in STE(A)M education: a review of literature from 2011 to 2020. Journal of Computing in Higher Education. DOI:https://doi.org/10.1007/s12528-022-09341-2
Li S., Ng K.-K., Lee L.-K. (2022).Progress Tracking and Online Learning Assisted by Social Media Tools: A Case Study of Teaching Architectural Design.2022 International Symposium on Educational Technology, ISET, p.113-117. DOI:https://doi.org/10.1109/ISET55194.2022.00031
Zou D., Xie H., Wang F.L. (2022).Effects of technology enhanced peer, teacher and self-feedback on students' collaborative writing, critical thinking tendency and engagement in learning. Journal of Computing in Higher Education. DOI:https://doi.org/10.1007/s12528-022-09337-y
Zou D., Xie H., Wang F.L. (2022).Effects of Scaffolded Peer Assessment on Students' Holistic Critical Thinking in Academic Writing.Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 13357 LNCS, p.147-156. DOI:https://doi.org/10.1007/978-3-031-08939-8_13
Lee C. (2022).Intention to use versus actual adoption of technology by university English language learners: what perceptions and factors matter? Computer Assisted Language Learning, v.35 n.8, p.2049-2077. DOI:https://doi.org/10.1080/09588221.2020.1857410
Luo L., Xie H., Rao Y., Wang F.L. (2019). Personalized recommendation by matrix co-factorization with tags and time information. Expert Systems with Applications, 2019, v. 119, p. 311-321.
DOI:https://doi.org/10.1016/j.eswa.2018.11.003
H., Zou D., Zhang R., Wang M., Kwan R. (2019). Personalized word learning for university students: a profile-based method for e-learning systems. Journal of Computing in Higher Education , 2019, v.31 n.2, p. 273-289. DOI:https://doi.org/10.1007/s12528-019-09215-0
Lee C., Yeung A.S., Cheung K.W. (2019). Learner perceptions versus technology usage: A study of adolescent English learners in Hong Kong secondary schools. Computers and Education, 2019, v.133, p.13-26. DOI:https://doi.org/10.1016/j.compedu.2019.01.005
Li K.C., Lee L.Y.-K., Wong S.-L., Yau I.S.-Y., Wong B.T.-M. (2019). The effects of mobile learning for nursing students: An integrative evaluation of learning process, learning motivation, and study performance. International Journal of Mobile Learning and Organisation, 2019, v.13 n.1, p. 51-67. DOI:https://doi.org/10.1504/IJMLO.2019.096471
Li K.C., Wong B.T.-M. (2019).How learning has been personalised: A review of literature from 2009 to 2018. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11546 LNCS, 2019, p. 72-81. DOI:https://doi.org/10.1007/978-3-030-21562-0_6
Lee L.-K., Cheung T.-K., Ho L.-T., Yiu W.-H., Wu N.-I. (2019). Learning computational thinking through gamification and collaborative learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, v.11546 LNCS, p.339-349. DOI:https://doi.org/10.1007/978-3-030-21562-0_28
Li K.C., Lee L.Y.-K., Wong S.-L., Yau I.S.-Y., Wong B.T.-M. (2019). Evaluation of mobile learning for the clinical practicum in nursing education: application of the FRAME model. Journal of Computing in Higher Education, 2019, v.31 n.2, p. 290-310. DOI:https://doi.org/10.1007/s12528-019-09213-2
Lee L.-K., Chau C.-H., Chau C.-H., Ng C.-T., Hu J.-H., Wong C.-Y., Yu L.-C., Wu N.-I. (2019). Improving the experience of teaching and learning kindergarten-level English vocabulary using augmented reality. International Journal of Innovation and Learning, 2019, v.25 n.2, p.110-125. DOI:https://doi.org/10.1504/IJIL.2019.097661
Zhong J., Xie H., Wang F.L. (2019). The research trends in recommender systems for e-learning: A systematic review of SSCI journal articles from 2014 to 2018. Asian Association of Open Universities Journal, 2019, v.14 n.1, p.12-27. DOI:https://doi.org/10.1108/AAOUJ-03-2019-0015
Li K.-C., Wong B.T.-M. (2019). The professional development needs for the use of educational technology: A survey of the Hong Kong academic community. Interactive Technology and Smart Education,2019, v.16 n.2, p.159-171. DOI:https://doi.org/10.1108/ITSE-10-2018-0089
Lee L.-K., Chau C.-P., Tsoi K.-N., Yang N.L., Wu N.-I. (2019). A mobile game for learning English vocabulary with augmented reality block builder. Communications in Computer and Information Science, 2019, v.1048, p.116-128. DOI:https://doi.org/10.1007/978-981-13-9895-7_11
H., Wang M., Zou D., Wang F.L. (2019). A personalized task recommendation system for vocabulary learning based on readability and diversity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, v. 11546 LNCS, p.82-92. DOI:https://doi.org/10.1007/978-3-030-21562-0_7
Leung K.-H., Hung K., Ko C.-P., Lo S.-F. (2019). Design and Development of an Augmented Reality Mobile Application for Medical Training. ICETAS 2019 – 2019 6th IEEE International Conference on Engineering, Technologies and Applied Sciences, 2019. DOI:https://doi.org/10.1109/ICETAS48360.2019.9117464
Qiu X. (2019). Picture or non-picture? The influence of narrative task types on lower- A nd higher-proficiency EFL learners’ oral production. IRAL – International Review of Applied Linguistics in Language Teaching, 2019. DOI:https://doi.org/10.1515/iral-2017-0094
Lui A.K.-F., Poon M.H.M., Wong R.M.H. (2019). Automated generators of examples and problems for studying computer algorithms: A study on students' decisions. Interactive Technology and Smart Education, 2019, v.16 n.3, p.204-218. DOI: https://doi.org/10.1108/ITSE-10-2018-0091
Wang F.L., Zhang R., Zou D., Au O., Xie H. (2019). On Hong Kong primary school english teachers’ acceptance of technology-enhanced language learning and teaching. 2019 International Symposium on Educational Technology. p.233-235. DOI:https://doi.org/10.1109/ISET.2019.00055
Au O.T.S. (2019). Student’s choice of learning medium does not affect performance but study regularity does. 2019 International Symposium on Educational Technology. p.258-261. DOI:https://doi.org/10.1109/ISET.2019.00061
Choi S.P.M., Lam S.S. (2019). iChecker: An efficient plagiarism detection tool for learning management systems. Scholarly Ethics and Publishing: Breakthroughs in Research and Practice, 2019, p.232-247. DOI:https://doi.org/10.4018/978-1-5225-8057-7.ch011
Tang F. (2019). Content Analysis Methodology: A Review on the Readiness on Science and Engineering Curriculum in Higher Education Institution in Supporting Undergraduates to Enter the Testing and Certification Industry. 2017 2nd International Symposium on Product Compliance Engineering. DOI:https://doi.org/10.1109/ISPCE-TW.2017.8626853
Boyer, E. (1990).Scholarship reconsidered: Priorities of the professoriate. Princeton, NJ: Carnegie Foundation for the Advancement of Teaching.
Boyer, E. (updated by D. Moser, T. C. Ream, & J. M. Braxton). (2015).Scholarship reconsidered: Priorities of the professoriate. San Francisco, CA: Jossey-Bass.
Haigh, N. (2010).The scholarship of teaching and learning: A practical introduction and critique.Auckland, New Zealand: National Centre for Tertiary Teaching Excellence.
Trigwell, K., Martin, E., Benjamin, J., & Prosser, M. (2000). Scholarship of teaching: A model. Higher Education Research and Development,19(2), 155–168.
