ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform

Ruipérez‐Valiente, José A.; Muñoz‐Merino, Pedro J.; Leony, Derick; Kloos, Carlos Delgado

doi:10.1016/j.chb.2014.07.002

Cited by 123 publications

(77 citation statements)

References 8 publications

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“…Such a focus on the progress of understanding is common among extent learning analytics. For example, Khan Academy provides analytics of learning activities to assess and demonstrate learning progress (Ruipérez-Valiente et al, 2014); intelligent tutoring systems also model understanding based on one's interactions with the tutor (Allen, Snow, & McNamara, 2015;Desmarais & Baker, 2012). Existing work in this area will inform the implementation of analytics to assess knowledge progress in KB.…”

Section: Progress-oriented Analyticsmentioning

confidence: 99%

Analytics for Knowledge Creation: Towards Epistemic Agency and Design-Mode Thinking

Chen

Zhang

2016

Learning Analytics

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Innovation and knowledge creation call for high-level epistemic agency and designmode thinking, two competencies beyond the traditional scopes of schooling. In this paper, we discuss the need for learning analytics to support these two competencies, and more broadly, the demand for education for innovation. We ground these arguments on a distinctive Knowledge Building pedagogy that treats education as a knowledge-creation enterprise. By critiquing current learning analytics for their focus on static-state knowledge and skills, we argue for agency-driven, choice-based analytics more attuned to higher order competencies in innovation. We further describe ongoing learning analytics initiatives that attend to these elements of design. Prospects and challenges are discussed, as well as broader issues regarding analytics for higher order competencies.

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Section: Progress-oriented Analyticsmentioning

confidence: 99%

Analytics for Knowledge Creation: Towards Epistemic Agency and Design-Mode Thinking

Chen

Zhang

2016

Learning Analytics

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“…The authors of 11 relevant studies not only published some benefits in peer-reviewed scholarly journals but they also cited many problems when trying to assess student learning through combinations of learning analytics, learning management system (LMS) activity data logs, and graded performance results (Agudo-Peregrina et al, 2014;Fidalgo-Blanco et al, 2015;Gomez-Aguilar et al, 2015;Iglesias-Pradas, Ruiz-de-Azcarate and Agudo-Peregrina, 2015;Nieto Acevedo and Montenegro Maran, 2015;Reyes, 2015;Ruiparez-Valiente et al, 2015;Scheffel et al, 2014;Xing et al, 2015;Yahya, Messoussi and Touahni, 2015).…”

Section: Introductionmentioning

confidence: 96%

“…1;Moodle, 2015). Other third-party learning analytics tools are available at cost and the free applications remain untested in Moodle (Hatala, Gasevic and Joksimovic, 2014;Nieto Acevedo and Montenegro Maran, 2015;Reyes, 2015;Ruiparez-Valiente et al, 2015;Yahya, Messoussi and Touahni, 2015). At the time of writing, there were no studies examining learning engagement module in Moodle. Several researchers recently studied how learning analytics in Moodle may be used to visualise student activity (Dimopoulos et al, 2013;Dyckhoff et al, 2012).…”

Section: Introductionmentioning

confidence: 98%

Can online student performance be forecasted by learning analytics?

Strang

2016

IJTEL

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The paper focuses on utilising learning analytics to assess student performance in an online business. The value of this paper is in the literature review and the process used for analysis since it provides a way of how research in Moodle learning analytics or other similar systems could be leveraged to track student progress and for retention. The engagement analytics module is a relatively new component of Moodle but it has not yet been investigated with respect to student performance or in online business courses. The purpose of this study was to examine the predictive relationships between student academic performance and Moodle engagement analytics indicators along with student online activity data from the system logs. Unfortunately none of the hypothesised learning analytics factors were positively related to, nor could they predict, student academic performance. However, several interesting deductions from the learning analytics data gave rise to ideas for further research. Sense making of puzzling statistics suggested a mediating pattern of students' poor self-regulation skills because more focus was put on the assignment requirements but less on interacting with the lesson materials needed to complete the assignment and thereby resulting in lower grades.

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“…Another important element of this case study is ALAS-KA that has been presented in previous work [37]. It is used …”

Section: Description and Calculation Of Optional Activitiesmentioning

confidence: 99%

Analyzing the Impact of Using Optional Activities in Self-Regulated Learning

Ruipérez‐Valiente

Muñoz‐Merino

Kloos

et al. 2016

IEEE Trans. Learning Technol.

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Abstract-Self-regulated learning (SRL) environments provide students with activities to improve their learning (e.g., by solving exercises), but they might also provide optional activities (e.g., changing an avatar image or setting goals) where students can decide whether they would like to use or do them and how. Few works have dealt with the use of optional activities in SRL environments. This paper thus analyzes the use of optional activities in two case studies with a SRL approach. We found that the level of use of optional activites was low with only 23.1 percent of students making use of some functionality, while the level of use of learning activities was higher. Optional activities which are not related to learning are used more. We also explored the behavior of students using some of the optional activities in the courses such as setting goals and voting comments, finding that students finished the goals they set in more than 50 percent of the time and that they voted their peers' comments in a positive way. We also found that gender and the type of course can influence which optional activities are used. Moreover, the relations of the use of optional activities with proficient exercises and learning gains is low when taking out third variables, but we believe that optional activities might motivate students and produce better learning in an indirect way.

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ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform

Cited by 123 publications

References 8 publications

Analytics for Knowledge Creation: Towards Epistemic Agency and Design-Mode Thinking

Analytics for Knowledge Creation: Towards Epistemic Agency and Design-Mode Thinking

Can online student performance be forecasted by learning analytics?

Analyzing the Impact of Using Optional Activities in Self-Regulated Learning

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