Incorporating video case study of mathematics teaching into professional development (PD) can provide opportunities for teachers to develop new ways of seeing teaching and learning and inform efforts to enact new instructional practices. However, more research is needed to understand how such PD can foster sustained teacher learning about…

Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are…

For many justifications, the collection, analysis, and use of educational data are central to the evaluation and improvement of students' progress and learning outcomes. The use of data in educational evaluation and decision making are expected to span all layers--from the institution, teachers, students, and classroom levels, providing a…

Scholars have applied automatic content analysis to study computer-mediated communication in computer-supported collaborative learning (CSCL). Since CSCL also takes place in face-to-face interactions, we studied the automatic coding accuracy of manually transcribed face-to-face communication. We conducted our study in an authentic higher-education…

Computational Thinking (CT) and creativity are considered two vital skills for the 21st century that should be incorporated into future curricula around the world. We studied the relationship between these two constructs while focusing on learners' personal characteristics. Two types of creativity were examined: creative thinking and computational…

In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…

The search for rigor in learning analytics applications has placed survey data in the suspect's corner, favoring more objective trace data. A potential lack of objectivity in survey data is the existence of response styles, the tendency of respondents to answer survey items in a particular biased manner, such as yeah saying or always disagreeing.…

To understand how learner metacognition and goal orientation affect learner problem-solving in a Serious Game (SG) environment, this study examined 12 undergraduate students' metacognition, goal orientations, and problem-solving performances and processes while playing a SG that adopts problem-based learning pedagogy to teach space science.…

Interactive digital tools increasingly used for language learning can provide detailed system logs (e.g., number of attempts, responses submitted), and thereby a window into the user's learning processes. To date, SLA researchers have made little use of such data to understand the relationships between learning conditions, processes, and outcomes.…

This study examines second language (L2) learners' perspectives regarding the affordances and challenges of using the Data-Driven Learning (DDL) to identify the properties of near-synonymous words. Employing a convergent mixed-method design, this study deciphers the perceptions of 40 undergraduate L2 learners majoring in English language teaching.…

During the COVID-19 pandemic period, all the Sri Lankan universities delivered lectures in fully online mode using Virtual Learning Environments. In fully online mode, students cannot track their performance level, their progress in the course, and their performances compared to the rest of the class. This paper presents research work conducted at…

Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…

This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…

Purpose: This study aims to uncover divergent collaboration in makerspaces using social network analysis to examine ongoing social relations and sequential data pattern mining to invesitgate temporal changes in social activities. Design/methodology/approach: While there is a significant body of qualitative work on makerspaces, there is a lack of…

This research was a mixed-methods study investigating how teachers in northeastern West Virginia use student data to drive their instructional decisions. This study also investigated teachers' perceptions of the data use on their instruction, their students, and themselves. Data collection for this research included both a cross-sectional survey…