Design of a learning dashboard to enhance reading outcomes and self-directed learning behaviors in out-of-class extensive reading

ABSTRACT

Self-directed learning (SDL) requires students to take initiative to learn and control their own learning process. Literature highlights the importance of SDL for lifelong learning. Yet, little understanding is known regarding how to support SDL at the school level, specifically for out-of-class learning context. To fill up this gap, this research developed a learning dashboard and integrated SDL process management in GOAL system. It was implemented to provide support for out-of-class online self-directed extensive reading (SDER) at a high school level. A two-group study conducted during a three-week spring vacation found the experimental group (N = 35, with SDL support) achieved significantly more reading outcomes than the control group (N = 12, without SDL support). Detailed GOAL interaction behavior analysis of the experimental group showed that viewing learning dashboard was significantly correlated with reading outcomes as well as interactions related to SDL process management. These findings highlights positive effect of SDL support in GOAL on students' out-of-class SDER outcomes as well as their SDL behaviors. The study provided implications for research related to extensive reading and SDL support for out-of-class learning.

KEYWORDS:

• Learning analytics
• self-directed learning
• self-direction
• learning dashboard
• extensive reading
• out-of-class learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by JSPS [grant number 16H06304], JSPS [grant number 22H03902], JSPS [grant number 20H01722], [grant number 20K20131] and New Energy and Industrial Technology Development Organization [grant number JPNP18013], [grant number JPNP20006].

Notes on contributors

Yuanyuan Yang

Yuanyuan Yang is a PhD candidate at the Graduate School of Informatics, Kyoto University. Her research interests include learning analytics, self-directed learning, learning performance prediction, educational data mining.

Rwitajit Majumdar

Rwitajit Majumdar is a senior lecturer at the Academic Center for Computing and Media Studies, Kyoto University. His research focuses on learning analytics and data-informed decision making in the teaching–learning context.

Huiyong Li

Huiyong Li is a post-doctoral researcher at the Academic Center for Computing and Media Studies, Kyoto University. His research focuses on learning analytics, self-directed learning, self-regulated learning, and technology-enhanced language learning.

Brendan Flanagan

Brendan Flanagan is a junior associate professor at the Academic Center for Computing and Media Studies, Kyoto University. His research focuses on text mining, machine learning, foreign language learning education.

Hiroaki Ogata

Hiroaki Ogata is a professor at the Academic Center for Computing and Media Studies and the Graduate School of Informatics at Kyoto University. His research includes computer supported ubiquitous and mobile learning, personalized and adaptive learning environments, mobile and embedded learning analytics, educational data mining, and educational data science.