透過您的圖書館登入
IP:3.15.2.28
  • 期刊

Applying Learning Analytics in Programming Courses: A Feasibility Analysis on VisCode

在程式語言課程中實施學習分析:VisCode的可行性分析

摘要


The commencement of Learning Analytics (LA) dates back to 2011 in response to the proliferation of Big Data. Its primary objective is to leverage data analysis outcomes with the goal of enhancing teaching and learning quality. Through the past decade, scholars have evolved LA concepts to incorporate Precision Education and Learning Analytics 2.0. Recently, Kyoto University introduced BookRoll, an e-book tool fortified with data collection capabilities. Researchers have utilized BookRoll's tracking logs to assess the efficacy of distance learning during the COVID-19 pandemic. This led to the enabling of new designs in learning activities, forecasts of at-risk students, unearthed students' learning strategies, and even organized dataset challenge events to foster research advancement. In summary, BookRoll can serve as a prototype for online learning environment research and development. The objective of this research is to evaluate the potential of VisCode programming software, as a means of supporting the development of Learning Analytics (LA) in programming courses. To this end, the study employs BookRoll as a benchmark for comparison. A total of 160 participants in programming courses were involved, and the data collected from them (the LBLS160 dataset) was reviewed. Additionally, the study analyzed the data challenge workshop that utilized this dataset. Based on the findings, it can be concluded that VisCode has the potential to contribute to the development of future LA research.

關鍵字

Learning analytics VisCode BookRoll

並列摘要


為了應對大數據的激增效益,學習分析(LA)的概念在2011年被提出。其主要目標是利用數據分析結果來提高教學品質。在過去的十年裡,學者們已經發展了學習實作,並且將其衍生出精準教育和學習分析2.0等新興概念。近年來,京都大學推出了BookRoll,這是一種具有數據收集功能的電子書工具。研究人員利用BookRoll的操作日誌來評估COVID-19大流行期間遠程學習的效果。這促進了學習活動、高危學生預測、挖掘學生的學習策略開發,甚至組織數據集挑戰活動以推進相關研究的進步性。綜上所述,BookRoll可以作為線上學習環境研發的原型。本研究的目的是評估VisCode程式開發工具作為支持學習分析基礎的潛力。為此,本研究採用BookRoll作為比較基準,共有160名程式語言課程參與者參與,並審查了從課程中收集的數據(稱為:LBLS160數據集)。此外,本研究分析了利用該數據集舉辦的數據挑戰研討會。根據這些發現,可以得出結論,VisCode有潛力為未來學習分析研究的發展做出貢獻。

並列關鍵字

Learning analytics VisCode BookRoll

參考文獻


Akçapınar, G., Hasnine, M. N., Majumdar, R., Flanagan, B., & Ogata, H. (2019). Developing an early-warning system for spotting at-risk students by using eBook interaction logs. Smart Learning Environments, 6(1), 1-15.
Akçapinar, G., Hasnine, N. M., Majumdar, R., Chen, A. M.-R., Flanagan, B., & Ogata, H. (2020). Exploring temporal study patterns in eBook-based learning. 28th International Conference on Computers in Education Conference Proceedings,
Bobea, M., Park, S., Flanagan, B., & Lu, O. H. (2023). Improving the Prediction Accuracy of Student Performance in a Cross-Semester Scenario Utilizing a Domain Adaptation Approach. Data Challange Workshop on the 13th International Learning Analytics & Knowledge Conference,
Chen, A. M.-R., Majumdar, R., Hwang, G.-J., Lin, Y.-H., Akçapınar, G., Flanagan, B., & Ogata, H. (2020). Improving EFL students’ learning achievements and behaviors using a learning analytics-based e-book system. Proceedings of 28th International Conference on Computers in Education Conference Proceedings,
Chen, C.-H., & Su, C.-Y. (2019). Using the BookRoll e-book system to promote self-regulated learning, self-efficacy and academic achievement for university students. Journal of Educational Technology & Society, 22(4), 33-46.

延伸閱讀