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Interpretable and Adaptable Early Warning learning analytics Model

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Computers, Materials & Continua 2022年第5期71卷 3211-3225页

作者： Shaleeza Sohail Atif Alvi Aasia Khanum The University of Newcastle Sydney2000Australia University of Management and Technology Lahore54770Pakistan Forman Christian College Lahore54600Pakistan

Major issues currently restricting the use of learning analytics are the lack of interpretability and adaptability of the machine learning models used in this *** makes it easy for the stakeholders to understand the working of these models and adaptability makes it easy to use the same model for multiple cohorts and courses in educational ***,some models in learning analytics are constructed with the consideration of interpretability but their interpretability is not ***,adaptability is not specifically considered in this *** paper presents a new framework based on hybrid statistical fuzzy theory to overcome these *** also provides explainability in the form of rules describing the reasoning behind a particular *** paper also discusses the system evaluation on a benchmark dataset showing promising *** measure of explainability,fuzzy index,shows that the model is highly *** system achieves more than 82%recall in both the classification and the context adaptation stages.

关键词： learning analytics interpretable machine learning fuzzy systems early warning interpretability explainable artificial intelligence

Exploring Students Engagement Towards the learning Management System (LMS) Using learning analytics

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Computer Systems Science & Engineering 2021年第4期37卷 73-87页

作者： Shahrul Nizam Ismail Suraya Hamid Muneer Ahmad A.Alaboudi Nz Jhanjhi Department of Information Systems Faculty of Computer Science&Information TechnologyUniversity MalayaKuala Lumpur50603Malaysia Department of Information systems College of Computer and Information SciencesShaqra UniversitySaudi Arabia School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya47500Malaysia

learning analytics is a rapidly evolving research discipline that uses theinsights generated from data analysis to support learners as well as optimize boththe learning process and environment. This paper studied students’ engagementlevel of the learning Management System (LMS) via a learning analytics tool,student’s approach in managing their studies and possible learning analytic methods to analyze student data. Moreover, extensive systematic literature review(SLR) was employed for the selection, sorting and exclusion of articles fromdiverse renowned sources. The findings show that most of the engagement inLMS are driven by educators. Additionally, we have discussed the factors inLMS, causes of low engagement and ways of increasing engagement factorsvia the learning analytics approach. Nevertheless, apart from recognizing thelearning analytics approach as being a successful method and technique for analyzing the LMS data, this research further highlighted the possibility of mergingthe learning analytics technique with the LMS engagement in every institution asbeing a direction for future research.

关键词： learning analytics student engagement learning management system systematic literature review

Requirement-driven Architecture for learning analytics:The Case of AT41 Project

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计算机教育 2021年第12期 201-209页

作者： Nesrine Zibani Ladjel Bellatreche Hassina El Kechai Sébastien Iksal with LIAS ISAE-ENSMAPoitiers86000France Techne Poitiers UniversityPoitiers86000France LIUM University of Le MansLaval53000France

Digital technologies are becoming present and essential in all sectors of our *** education,the intensive usage of digital learning devices contributes to generating a large amount of trace data from digital learning *** exploitation of these traces represents a valuable asset for both device producers(to improve the design of the devices)and consumers(learners and teachers).In this paper,we first share our vision for better exploitation by teachers,of traces from middle schoolers’digital activities generated by their use of tools and digital learning services during different *** vision is a part of the AT41 project funded by the French Ministry of *** exploitation has to meet the requirements of the different *** such a project is not an easy task,because it has to consider the following issues:①the lack of comprehensive and clear methodology to design and exploit these traces;①heterogeneity of teacher requirements that complicates their elicitation and analysis;①the diversity of trace ***,we propose a requirement-driven architecture for learning analytics composed of a well-identified life *** architecture is augmented by learner *** offers a repository storing both teacher requirements and traces to facilitate the learning analytics in generating relevant and valuable indicators.

关键词： dashboard learning analytics trace exploitation requirements

Chilean University Students Digital learning Technology Usage Patterns and Approachesto learning

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ECNU Review of Education 2022年第1期5卷 37-64页

作者： Carlos González Dany Lópeza Lina Calle-Arangoa Helena Montenegro Paula Clasing Pontificia Universidad Catolica de Chile-Millennium Nucleus Universidad de Chile-Millennium Nucleus University of Michigan

Purpose:This study aims to explore Chilean students'digital technology usage patterns andapproaches to learningDesignlApproach/Methods:We conducted this study in two stages We worked with onesemester learning management systems(LMS),library,and students records data in the *** performed a k-means cluster analysis to identify groups with similar usage *** second stage,we invited students from emerging dusters to participate in group *** analysis was employed to analyze ***:Three groups were identified:ID digital library users/high performers,who adopteddeeper approaches to learning obtained higher marks,and used learning resources to integratematerials and expand understanding 2)LMS and physical library userslmid-performers,whoadopted mainly strategicapproaches obtained marks dlose to average,and used learning resources for studying in an organized manner toget good marks and 3)lower users of LMS andlibrarylmidlow performers,who adopted mainly a surface approach,obtained mid-to-lower-than-averagemarks,and used learning resources for minimum content understanding Originality/Value:We demonstrated the importance of combining learning analytics data withqualitative methods to make sense of digital technology usage patternss approaches to learningare associated with learning resources *** recommendations are presented.

关键词： Academic performance approaches to learning digital technology learning analytics

A Study of learning Behavioral Engagement in Live Teaching

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Frontiers of Education in China 2022年第1期17卷 69-99页

作者： LIU Sizhuo LI Shuang HUANG Jiajing Institute of Education University College LondonLondon WC1H 0ALUK Distance Education Research Center School of Educational TechnologyBeijing Normal UniversityBeijing 100875China

Based on the related theories and research results of learning behavioral engagement,this study constructed an evaluation framework of learning behavioral engagement in live teaching,which included 24 indicators in three dimensions:compliance with norms,learning participation and social participation.A small-class live English learning for younger students on the ClassIn was taken as a case study *** younger students attended this English learning course of 16 lessons totaling 950 *** preset indicators were preliminarily examined based on the teaching records and the recorded course ***,experts in the field of educational technology were invited to develop the learning behavioral engagement dimensions and indicator weightings by using the Analytic Hierarchy Process,and to determine the evaluation indicator system for the evaluation of learning behavioral ***,based on this framework,the characteristics of learning behavioral engagement of the case course were analyzed,and the influences of students’individual factors,teaching and environmental factors on learning behavioral engagement in live teaching were investigated.

关键词： live teaching live learning live learning behaviors live learning evaluation evaluation indicators influencing factors analytic hierarchy process learning analytics

A Study of Detecting Student Engagement Modes in an Online learning Platform

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Frontiers of Education in China 2022年第1期17卷 23-45页

作者： XIAO Rui LIU Qianhui SHANG Junjie HUANG Win-bin learning Science Laboratory Graduate School of EducationPeking UniversityBeijing 100871China Department of Information Management Peking UniversityBeijing 100871China

In this paper,we used the platform log data to extract three features(proportion of passive video time,proportion of active video time,and proportion of assignment time)aligning with different learning activities in the Interactive-Constructive-Active-Passive(ICAP)framework,and applied hierarchical clustering to detect student engagement modes.A total of 840 learning rounds were clustered into four categories of engagement:passive(n=80),active(n=366),constructive(n=75)and resting(n=319).The results showed that there were differences in the performance of the four engagement modes,and three types of learning status were identified based on the sequences of student engagement modes:difficult,balanced and *** study indicated that based on the ICAP framework,the online learning platform log data could be used to automatically detect different engagement modes of students,which could provide useful references for online learning analysis and personalized learning.

关键词： online learning platform online learning student engagement Interactive-Constructive-Active-Passive(ICAP)framework hierarchical clustering learning analytics log analysis

Students’ Numeracy and Literacy Aptitude Analysis and Prediction Using Machine learning

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Journal of Computer and Communications 2022年第8期10卷 90-103页

作者： Tianyu Li St. George’s School Vancouver Canada

Education is one of the most pivotal services in societal development as it cultivates a wide variety of skills, especially numeracy and literacy skills. However, students may have varying masteries of these two aptitudes. Some attribute this to students’ intrinsic efforts while others attribute this to students’ capabilities and affiliated environments. In this work, I explore the numeracy and literacy aptitude patterns of students from various cultures based on a dataset that contains various demographic information, from which I deduced some preliminary trends. After the comparison of numerous machine learning algorithms, the optimal algorithm or combination of a few algorithms predicts students’ performances by classifying students of different backgrounds into various potential outcomes. The results suggest that proper resources and supports are necessary for enhanced learning.

关键词： Numeracy and Literacy Machine learning learning analytics Classification

PerformanceVis:Visual analytics of student performance data from an introductory chemistry course

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Visual Informatics 2019年第4期3卷 166-176页

作者： Haozhang Deng Xuemeng Wang Zhiyi Guo Ashley Decker Xiaojing Duan Chaoli Wang G.Alex Ambrose Kevin Abbott University of Rochester RochesterNY 14627United States Fudan University Shanghai 200433China University of Notre Dame Notre DameIN 46556United States

We present PerformanceVis,a visual analytics tool for analyzing student admission and course performance data and investigating homework and exam question *** a university-wide introductory chemistry course with nearly 1000 student enrollment,we consider the requirements and needs of students,instructors,and administrators in the design of *** study the correlation between question items from assignments and exams,employ machine learning techniques for student grade prediction,and develop an interface for interactive exploration of student course performance *** includes four main views(overall exam grade pathway,detailed exam grade pathway,detailed exam item analysis,and overall exam&homework analysis)which are dynamically linked together for user interaction and *** demonstrate the effectiveness of PerformanceVis through case studies along with an ad-hoc expert ***,we conclude this work by pointing out future work in this direction of learning analytics research.

关键词： Student performance Item analysis Grade prediction learning analytics Knowledge discovery

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