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5th European Conference on Software Engineering Education (ECSEE)

作者： Sapsai, Iryna Valencia, Yeimy Abke, Joerg Univ Appl Sci Aschaffenburg Fac Engn Aschaffenburg Germany

ISBN: (纸本)9781450399562

In this article, the authors describe a prototype of a learning analytics dashboard (LAD) for educators. It is based on the analysis of pedagogical actions and taking into the process and learning style of students in an online environment based on learning analytics (LA). A description of the dashboard structure, divided into levels and categories based on available learning analytics, will allow the educator to dive deeper into the online course themselves and explore more. It will also allow them to determine the level of student performance, identify gaps in learning materials, and research student data. The authors have identified further directions for the development of a LAD for a professor, including modeling algorithms for researching student behavior and learning style using Artificial Intelligence and presenting LA in a visualized form. This paper shows the stages of creating a professor's LAD prototype as a functional part of the adaptive learning system in the HASKI-System to analyze visual information obtained from LA and the possibilities to monitor the learning process, learning progress, student activity, and make decisions on careful intervention in the students' learning process.

关键词： learning analytics dashboard learning analytics information visualization pedagogical knowledge pedagogical actions distance education pedagogy adaptive learning system

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Self-service Teacher-facing learning analytics dashboard with Large Language Models 25

Self-service Teacher-facing Learning Analytics Dashboard wit...

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15th International Conference on learning analytics and Knowledge

作者： Wang, Zuo Lin, Weiyue Hu, Xiao Univ Hong Kong Hong Kong Peoples R China Univ Arizona Tucson AZ USA

ISBN: (纸本)9798400707018

With the rise of online learning platforms, the need for effective learning analytics (LA) has become critical for teachers. However, the development of traditional LA dashboards often requires technical expertise and a certain level of data literacy, preventing many teachers from integrating LA dashboards effectively and flexibly into their teaching practice. This paper explores the development of a self-service teacher-facing learning analytics dashboard powered by large language models (LLMs), for improving teaching practices. By leveraging LLMs, the self-service system aims to simplify the implementation of data queries and visualizations, allowing teachers to create personalized LA dashboards using natural languages. This study also investigates the capabilities of LLMs in generating charts for LA dashboards and evaluates the effectiveness of the self-service system through usability tests with 15 teachers. Preliminary findings suggest that LLMs demonstrate high capabilities in generating charts for LA dashboards, and the LLM-powered self-service system can effectively address participating teachers' pedagogical needs for LA. This research contributes to the ongoing research on the intersection of LLMs and education, emphasizing the potential of self-service systems to empower teachers in daily teaching practices.

关键词： learning analytics dashboard self-service learning analytics large language models data visualization

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VisOJ: real-time visual learning analytics dashboard for online programming judge

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VISUAL COMPUTER 2023年第6期39卷 2393-2405页

作者： Fu, Qian Bai, Xue Zheng, Yafeng Du, Runsheng Wang, Dongqing Zhang, Tianyi Beijing Normal Univ Fac Educ Sch Educ Technol Beijing Peoples R China Henan Univ Econ & Law Sch Math & Informat Sci Zhengzhou Peoples R China Beijing Normal Univ Zhuhai Inst Adv Studies Humanities & Social Sci Zhuhai Peoples R China Henan Univ Econ & Law Sch Comp & Informat Engn Zhengzhou Peoples R China Univ Penn Sch Engn & Appl Sci Philadelphia PA 19104 USA

Online Judge (OJ) is an important aid for programming learning that can help students evaluate learning effects in real-time, while teachers can adjust practice tasks in time according to the records of the tool. With these advantages, OJ shows great value for promoting teaching and learning in programming. The existing OJ system usually only provides information such as problem status list and recent rank list. However, it is unable to provide teachers with more fine-grained analysis information, such as the distribution of students' incorrect responses and level of knowledge mastery. And it also cannot provide students with effective comparative information on their learning status. This research developed a visual learning analytics dashboard named VisOJ for the OJ system, which includes two types of user interfaces: teacher and student. The teacher interface presents students' learning status and ranking trends, which help teachers monitor and give feedback on their learning activities. The student interface provides views such as error type analysis and evaluation, which promote students' self-reflection and self-regulation. Preliminary case studies and expert interviews prove the usability of the dashboard. In the end, we summarize our main work and suggest future research directions.

关键词： learning analytics dashboard Online judge Visual analytics Programming study

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Chatting with a learning analytics dashboard: The Role of Generative AI Literacy on Learner Interaction with Conventional and Scaffolding Chatbots 25

Chatting with a Learning Analytics Dashboard: The Role of Ge...

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15th International Conference on learning analytics and Knowledge

作者： Jin, Yueqiao Yang, Kaixun Yan, Lixiang Echeverria, Vanessa Zhao, Linxuan Alfredo, Riordan Milesi, Mikaela Fan, Jie Xiang Li, Xinyu Gasevic, Dragan Martinez-Maldonado, Roberto Monash Univ Clayton Vic Australia Escuela Super Politecn Litoral Guayaquil Ecuador

ISBN: (纸本)9798400707018

learning analytics dashboards (LADs) simplify complex learner data into accessible visualisations, providing actionable insights for educators and students. However, their educational effectiveness has not always matched the sophistication of the technology behind them. Explanatory and interactive LADs, enhanced by generative AI (GenAI) chatbots, hold promise by enabling dynamic, dialogue-based interactions with data visualisations and offering personalised feedback through text. Yet, the effectiveness of these tools may be limited by learners' varying levels of GenAI literacy, a factor that remains underexplored in current research. This study investigates the role of GenAI literacy in learner interactions with conventional (reactive) versus scaffolding (proactive) chatbot-assisted LADs. Through a comparative analysis of 81 participants, we examine how GenAI literacy is associated with learners' ability to interpret complex visualisations and their cognitive processes during interactions with chatbot-assisted LADs. Results show that while both chatbots significantly improved learner comprehension, those with higher GenAI literacy benefited the most, particularly with conventional chatbots, demonstrating diverse prompting strategies. Findings highlight the importance of considering learners' GenAI literacy when integrating GenAI chatbots in LADs and educational technologies. Incorporating scaffolding techniques within GenAI chatbots can be an effective strategy, offering a more guided experience that reduces reliance on learners' GenAI literacy.

关键词： learning analytics dashboard generative AI literacy generative AI chatbots data visualisation

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How do visualizations and automated personalized feedback engage professional learners in a learning analytics dashboard? 24

How do visualizations and automated personalized feedback en...

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14th Annual International Conference on learning analytics and Knowledge (LAK) - learning analytics in the Age of Artificial Intelligence

作者： Alcock, Sarah Rienties, Bart Aristeidou, Maria Mostefaoui, Soraya Kouadri Open Univ Inst Educ Technol Milton Keynes Bucks England Open Univ Comp & Commun Milton Keynes Bucks England

ISBN: (纸本)9798400716188

learning analytics dashboards (LAD) are the subject of research in a multitude of schools and higher education institutions, but a lack of research into learner-facing dashboards in professional learning has been identified. This study took place in an authentic professional learning context and aims to contribute insights into LAD design by using an academic approach in a practice-based environment. An existing storytelling LAD created to support 81 accountants was evaluated using Technology Acceptance Model, finding a learner expectation for clarity, conciseness, understanding and guidance on next steps. High usage levels and a 'take what you need' approach was identified, with all visualizations and automated personalized feedback being considered useful although to varying degrees. Professional learners in this study focus on understanding and acting upon weaknesses rather than celebrating strengths. The lessons for LAD design are to offer choice and create elements which support learners to take action to improve performance at a multitude of time points and levels of success.

关键词： learning analytics dashboard LAD professional learning Technology Acceptance Model assessment feedback data storytelling personalization accountancy

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Preliminary Evaluation of learning analytics dashboard for College Teachers' Online Professional learning 24

Preliminary Evaluation of Learning Analytics Dashboard for C...

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24th IEEE International Conference on Advanced learning Technologies (ICALT)

作者： Wang, Chao Ng, Jeremy Tzi Dong Lopez, Nora Patricia Hernandez Hu, Xiao Univ Hong Kong Hong Kong Peoples R China Southern Univ Sci & Technol Hong Kong Peoples R China Univ Hong Kong Fac Educ Hong Kong Peoples R China

ISBN: (纸本)9798350362060;9798350362053

Widely accessible online courses provide a feasible platform for teachers' continuous online professional learning. The learning analytics dashboard (LAD) provides fine-grained and actionable feedback that supports learners' self-regulated learning. However, previous studies on LAD design and evaluation predominantly focused on student-facing LADs, with scarce attention on LADs designed for teacher-learners. This study introduces the LAD in an online learning platform for college teachers and conducts a preliminary evaluation with 18 participants. Results show their largely positive ratings on five criteria (e.g., perceived usefulness, ease of use, and behavioral changes) and offer feedback for further refinements of the LAD. This study will improve our understanding of LA-enabled teacher online professional learning and provide practical implications for designing and evaluating LA tools catered to teacher-learners.

关键词： learning analytics dashboard teacher online professional learning preliminary evaluation

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Mediating Teacher Professional learning with a learning analytics dashboard and Training Intervention

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TECHNOLOGY KNOWLEDGE AND learning 2023年第3期28卷 981-998页

作者： Khulbe, Manisha Tammets, Kairit Tallinn Univ Tallinn Estonia

Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of learning data can, theoretically, aid teachers in data use, but often fall short of their potential as they are commonly designed without reference to educational theory and rarely consider end-user's needs. Keeping these challenges in mind, we designed a professional development program that aimed at, among other things, improving teachers' beliefs regarding data and their data literacy skills. After the training, we found that teachers had more positive attitudes regarding data. However, some data literacy skills proved quite difficult to learn. We present and analyse our intervention here and forward a proposal for improving the effectiveness of data use interventions by leveraging theory-based learning analytics (LA) dashboards as mediating tools that scaffold teachers' acquisition of new knowledge and skills during and beyond the intervention.

关键词： Teachers' data use Data use intervention learning analytics learning analytics dashboard Teacher-facing dashboard Engagement

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Adaptive or adapted to: Sequence and reflexive thematic analysis to understand learners' self-regulated learning in an adaptive learning analytics dashboard

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BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY 2023年第1期54卷 98-125页

作者： Park, Eunsung Ifenthaler, Dirk Clariana, Roy B. Tennessee Technol Univ Dept Curriculum & Instruct Cookeville TN 38505 USA Univ Mannheim Learning Design & Technol Mannheim Germany Curtin Univ Data Sci Higher Educ Learning & Teaching Bentley WA Australia Penn State Univ Dept Learning & Performance Syst University Pk PA 16802 USA

The real-time and granularized learning information and recommendations available from adaptive learning technology can provide learners with feedback that is personalized. However, at an individual level, learners often experience technological and pedagogical conflicts. Learners have more freedom to accept, ignore or reject the feedback while also having the challenges of building learning strategies and utilizing learning information that requires self-regulated learning skills. Given the conflicts, both understanding how learners learn and providing support for learners to be more self-regulated in the learning environment are imperative. This investigation explores how learners processed their learning in an adaptive technology-integrated learning analytics dashboard (ALAD). It employed mixed-methods using a lens of self-regulated learning (SRL). Three groups were identified based on clustering analysis of the learners' usage of warm-up (WU) tests. Sequence analysis revealed the time trends of each group's interactions with course content. Reflexive thematic analysis brought insights on how learners built their learning strategies (eg, ways of using WU tests and submodule assessments) and how they monitored and controlled their learning. It showed their dynamic interactions with core adaptive learning analytics dashboard elements. Challenges such as difficulties in rehearsing and monitoring through segmented course content arose from the new structural changes. We suggest the need of future improvement to individual learning support through the learning analytics dashboard to be more diverse and dynamic (real-time) over the course of learning while reducing potential undesirable consequences. Practitioner notes What is already known about this topic One purpose of learning analytics and adaptive learning is to help learners identify learning goals and take action to achieve their goals. learning analytics intervention showed support in learners' reflection phas

关键词： adaptive learning clustering analysis learning analytics dashboard reflexive thematic analysis self-regulated learning sequence analysis

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Ready or not? Investigating in-service teachers' integration of learning analytics dashboard for assessing students' collaborative problem solving in K-12 classrooms

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EDUCATION AND INFORMATION TECHNOLOGIES 2025年第2期30卷 1745-1776页

作者： Liu, Yiming Hu, Xiao Ng, Jeremy Tzi Dong Ma, Zhengyang Lai, Xiaoyan Univ Hong Kong Fac Educ Hong Kong Peoples R China Hong Kong Univ Sci & Technol Guangzhou Computat Media & Arts Thrust Guangzhou Peoples R China Guangdong Polytech Normal Univ Sch Educ Sci Guangzhou Peoples R China

Collaborative problem solving (CPS) has emerged as a crucial 21st century competence that benefits students' studies, future careers, and general well-being, prevailing across disciplines and learning approaches. Given the complex and dynamic nature of CPS, teacher-facing learning analytics dashboards (LADs) have increasingly been adopted to support teachers' CPS assessments by analysing and visualising various dimensions of students' CPS. However, there is limited research investigating K-12 teachers' integration of LADs for CPS assessments in authentic classrooms. In this study, a LAD was implemented to assist K-12 teachers in assessing students' CPS skills in an educational game. Based on the person-environment fit theory, this study aimed to (1) examine the extent to which teachers' environmental and personal factors influence LAD usage intention and behaviour and (2) identify personal factors mediating the relationships between environmental factors and LAD usage intention and behaviour. Survey data of 300 in-service teachers from ten Chinese K-12 schools were collected and analysed using partial least squares structural equation modelling (PLS-SEM). Results indicated that our proposed model showed strong in-sample explanatory power and out-of-sample predictive capability. Additionally, subjective norms affected technological pedagogical content knowledge (TPACK) and self-efficacy, while school support affected technostress and self-efficacy. Moreover, subjective norms, technostress, and self-efficacy predicted behavioural intention, while school support, TPACK, and behavioural intention predicted actual behaviour. As for mediation effects, school support indirectly affected behavioural intention through self-efficacy, while subjective norms indirectly affected behavioural intention through self-efficacy and affected actual behaviour through TPACK. This study makes theoretical, methodological, and practical contributions to technology integration in general and

关键词： 21st century skills Collaborative problem solving learning analytics dashboard Technology integration Person-environment fit K-12 teachers

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A learning analytics dashboard for data-driven recommendations on influences of non-cognitive factors in introductory programming

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EDUCATION AND INFORMATION TECHNOLOGIES 2024年第8期29卷 9221-9256页

作者： Kaur, Amanpreet Chahal, Kuljit Kaur Guru Nanak Dev Univ Dept Comp Sci Amritsar Punjab India

Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a dashboard to understand the contribution of introductory programming students' learning motivation, personality, and class participation factors to their programming performance and provide adaptive support to improve their motivation and persistence. Moreover, this study evaluates the effectiveness and usefulness of the dashboard in two phases: committee evaluation and laypersons evaluation. The evaluation results indicate dashboard's effectiveness in students' better-informed decision-making related to their learning approach. In both phases, the dashboard has been perceived as useful and easy-to-use tool. These findings indicate that the dashboard is perceived as a useful tool for providing timely feedback about non-cognitive factors contributing to students' programming performance. The study provides insights into the noncognitive side of novice programmers and encourages further exploration of other aspects influencing their performance.

关键词： Introductory Programming course learning analytics dashboard Personality traits Motivational factors Class participation Performance prediction Data-driven recommendations

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