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Onur Karademir; Lena Borgards; Daniele Di Mitri; Sebastian Strauß; Marcus Kubsch; Markus Brobeil; Adrian Grimm; Sebastian Gombert; Nikol Rummel; Knut Neumann; Hendrik Drachsler – Journal of Learning Analytics, 2024
This paper presents a teacher dashboard intervention study in secondary school practice involving teachers (n = 16) with their classes (n = 22) and students (n = 403). A quasi-experimental treatment-control group design was implemented to compare student learning outcomes between classrooms where teachers did not have access to the dashboard and…
Descriptors: Learning Analytics, Intervention, Educational Technology, Secondary School Students
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
Dana AlZoubi; Evrim Baran – Journal of Learning Analytics, 2024
There is a growing interest in the research and use of automated feedback dashboards that display classroom analytics; yet little is known about the detailed processes instructors use to make sense of these tools, and to determine the impact on their teaching practices. This research was conducted at a public Midwestern university within the…
Descriptors: Learning Analytics, College Faculty, Technology Uses in Education, Educational Technology
Rafael Ferreira Mello; Elyda Freitas; Luciano Cabral; Filipe Dwan Pereira; Luiz Rodrigues; Mladen Rakovic; Jackson Raniel; Dragan Gaševic – Journal of Learning Analytics, 2024
Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…
Descriptors: Literature Reviews, Learning Analytics, Natural Language Processing, Data Collection
Stanislav Pozdniakov; Jonathan Brazil; Mehrnoush Mohammadi; Mollie Dollinger; Shazia Sadiq; Hassan Khosravi – Journal of Learning Analytics, 2025
Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…
Descriptors: Student Evaluation, Artificial Intelligence, Student Developed Materials, Feedback (Response)
Rets, Irina; Herodotou, Christothea; Gillespie, Anna – Journal of Learning Analytics, 2023
The progressive move of higher education institutions (HEIs) towards blended and online environments, accelerated by COVID-19, and their access to a greater variety of student data has heightened the need for ethical learning analytics (LA). This need is particularly salient in light of a lack of comprehensive, evidence-based guidelines on ethics…
Descriptors: Ethics, Learning Analytics, Evidence Based Practice, Guidelines
Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
Lixiang Yan; Linxuan Zhao; Dragan Gaševic; Xinyu Li; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2023
Socio-spatial learning analytics (SSLA) is an emerging area within learning analytics research that seeks to uncover valuable educational insights from individuals' social and spatial data traces. These traces are captured automatically through sensing technologies in physical learning spaces, and the research is commonly based on the theoretical…
Descriptors: Learning Analytics, Educational Research, Social Behavior, Physical Environment
Knight, Simon; Abel, Sophie; Shibani, Antonette; Goh, Yoong Kuan; Conijn, Rianne; Gibson, Andrew; Vajjala, Sowmya; Cotos, Elena; Sándor, Ágnes; Shum, Simon Buckingham – Journal of Learning Analytics, 2020
Writing analytics has emerged as a sub-field of learning analytics, with applications including the provision of formative feedback to students in developing their writing capacities. Rhetorical markers in writing have become a key feature in this feedback, with a number of tools being developed across research and teaching contexts. However,…
Descriptors: Rhetoric, Documentation, Writing (Composition), Learning Analytics
Dickler, Rachel; Gobert, Janice; Sao Pedro, Michael – Journal of Learning Analytics, 2021
Educational technologies, such as teacher dashboards, are being developed to support teachers' instruction and students' learning. Specifically, dashboards support teachers in providing the just-in-time instruction needed by students in complex contexts such as science inquiry. In this study, we used the Inq-Blotter teacher-alerting dashboard to…
Descriptors: Educational Technology, Science Education, Science Process Skills, Intelligent Tutoring Systems
Holstein, Kenneth; McLaren, Bruce M.; Aleven, Vincent – Journal of Learning Analytics, 2019
Involving stakeholders throughout the creation of new educational technologies can help ensure their usefulness and usability in real-world contexts. However, given the complexity of learning analytics (LA) systems, it can be challenging to meaningfully involve non-technical stakeholders throughout their design and development. This article…
Descriptors: Learning Analytics, Technology Uses in Education, Artificial Intelligence, Stakeholders
Olney, Tom; Walker, Steve; Wood, Carlton; Clarke, Anactoria – Journal of Learning Analytics, 2021
Most higher education institutions view their increasing use of learning analytics as having significant potential to improve student academic achievement, retention outcomes, and learning and teaching practice but the realization of this potential remains stubbornly elusive. While there is an abundance of published research on the creation of…
Descriptors: Learning Analytics, Higher Education, STEM Education, College Faculty
Victor Manuel Corza-Vargas; Roberto Martinez-Maldonado; Boris Escalante-Ramirez; Jimena Olveres – Journal of Learning Analytics, 2024
While teachers often monitor and adjust their learning design based on students' emotional states in physical classrooms, synchronous online environments often limit their ability to perceive the emotional climate of the class. Drawing from the concept of social translucence, it is suggested that making students' emotional states…
Descriptors: Foreign Countries, Undergraduate Students, Privacy, Cultural Awareness
Campos, Fabio C.; Ahn, June; DiGiacomo, Daniela K.; Nguyen, Ha; Hays, Maria – Journal of Learning Analytics, 2021
With the spread of learning analytics (LA) dashboards in K-12 schools, educators are increasingly expected to make sense of data to inform instruction. However, numerous features of school settings, such as specialized vantage points of educators, may lead to different ways of looking at data. This observation motivates the need to carefully…
Descriptors: Middle School Teachers, Mathematics Teachers, Learning Analytics, Comprehension