Development of Open Textbooks Learning Analytics System

Prasad, Deepak; Totaram, Rajneel; Usagawa, Tsuyoshi

doi:10.19173/irrodl.v17i5.2541

Cited by 6 publications

(5 citation statements)

References 35 publications

(24 reference statements)

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“…Track individual learners' online and offline interactions with open learning resources Prasad et al (2016) 43. University of Wollongong Analysis, intervention, reflection Visualize patterns of student interactions on discussion forums Allow instructors to identify at-risk students and potentially high and low performing students for planning interventions, and the extent to which a learner community is developing in a class Mat et al (2013) Table AI.…”

Section: Monitoringmentioning

confidence: 99%

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Learning analytics in higher education: an analysis of case studies

Wong

2017

AAOUJ

107

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Purpose-The purpose of this paper is to present a systematic review of the mounting research work on learning analytics. Design/methodology/approach-This study collects and summarizes information on the use of learning analytics. It identifies how learning analytics has been used in the higher education sector, and the expected benefits for higher education institutions. Empirical research and case studies on learning analytics were collected, and the details of the studies were categorized, including their objectives, approaches, and major outcomes. Findings-The results show the benefits of learning analytics, which help institutions to utilize available data effectively in decision making. Learning analytics can facilitate evaluation of the effectiveness of pedagogies and instructional designs for improvement, and help to monitor closely students' learning and persistence, predict students' performance, detect undesirable learning behaviours and emotional states, and identify students at risk, for taking prompt follow-up action and providing proper assistance to students. It can also provide students with insightful data about their learning characteristics and patterns, which can make their learning experiences more personal and engaging, and promote their reflection and improvement. Originality/value-Despite being increasingly adopted in higher education, the existing literature on learning analytics has focussed mainly on conventional face-to-face institutions, and has yet to adequately address the context of open and distance education. The findings of this study enable educational organizations and academics, especially those in open and distance institutions, to keep abreast of this emerging field and have a foundation for further exploration of this area.

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Section: Monitoringmentioning

confidence: 99%

“…open source resources could be modified and adapted by anyone to meet specific user needsPrasad et al (2016) University of Sydney LA features such as instant feedback and auto-grading are especially useful for instructors teaching subjects in computer science educationGramoli et al (2016) …”

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confidence: 99%

Learning analytics in higher education: an analysis of case studies

Wong

2017

AAOUJ

107

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“…Another approach to providing value with relatively low effort is instrumenting already existing resources, as Prasad et al (2016) have shown by developing an epub (an electronic book format) viewer to monitor interactions similarly to how a MOOC does; many courses in schools use books that are available as PDFs, therefore instrumenting such books may provide clickstream-like information on reading habits without the requirement to redevelop course resources. In addition, for those subjects that perform field studies, techniques from mobile learning may be adapted, with success shown if the developed applications actually support the student in their learning goals required by the existing course content while providing LA data (Fulantelli et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Input Determination for Models Used in Predicting Student Performance

Krumins¹,

Cakula²

2020

BJMC

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To capture and code as much as possible of student behavior and environment to apply learning analytics in conventional classrooms, patterns among successful inputs of existing online learning / learning management systems can be identified, to find existing but uncaptured classroom data. The goal of this review is to suggest proposals on expanded use of learning analytics in traditional classrooms. Predictors from learning models used in online learning can be applied to the traditional classroom and analogues may be found for unavailable predictors. Approaches used in developing these predictors can be used to develop predictors for conventional classrooms. Existing data can be used, or data that is convenient may be captured, with emphasis on approaches that work on smaller groups, where training of individual models should be attempted. The data collected should be simple to obtain, support the users otherwise, or have provable benefits.

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“…Lockyer, Heathcote, and Dawson (2013) analyze how analytics can facilitate pedagogical actions for learning designs. Another study highlights that LA may provide insights on how to assess students based on the OERs’ impact (Prasad, Totaram, & Usagawa, 2016). However, Persico and Pozzi (2015) argue that most of the research in learning analytics has concentrated attention to the contribution of learning analytics during the enactment of learning experiences and not in a design phase.…”

Section: Theoretical Background and Related Workmentioning

confidence: 99%

Evaluation of a learning analytics tool for supporting teachers in the creation and evaluation of accessible and quality open educational resources

Avila¹,

Baldiris²,

Fabregat³

et al. 2020

Brit J Educational Tech

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The learning analytics (LA) field seeks to analyze data about students’ interactions, and it has been applied in the development of tools for supporting both learning and teaching processes. Recent research has paid attention on how LA may benefit teachers in the creation of educational resources. However, most of the research on LA solutions is carried out to support teachers in analyzing students’ behavior data collected as they interact with virtual learning environments. While solutions to support teachers in different virtual learning and teaching contexts have become important, to date little research has been done on how LA solutions can help teachers to create and evaluate Open Educational Resources (OERs). This study aims at presenting the evaluation of a LA tool for supporting teachers in the creation and evaluation of accessible and quality OERs considering that both processes fall within the competences that teachers can acquire and strengthen by participating as authors (creation) and evaluators (evaluation) of OERs. The study was conducted with Colombian teachers and the results obtained highlight the positive effect the tool had on the teachers’ acquisition of the competences and the positive attitude they had toward using the tool.

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Development of Open Textbooks Learning Analytics System

Cited by 6 publications

References 35 publications

Learning analytics in higher education: an analysis of case studies

Learning analytics in higher education: an analysis of case studies

Input Determination for Models Used in Predicting Student Performance

Evaluation of a learning analytics tool for supporting teachers in the creation and evaluation of accessible and quality open educational resources

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