The rise of massive open online courses (MOOCs) brings rich opportunities for understanding learners' experiences based on analyzing learner-generated content such as course reviews. Traditionally, the unstructured textual data is analyzed qualitatively via manual coding, thus failing to offer a timely understanding of the learner's experiences.…

Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…

Providing coaching to participants in inquiry-based online discussions contributes to developing cognitive presence (CP) and higher-order thinking. However, a primary issue limiting quality and timely coaching is instructors' lack of tools to efficiently identify CP phases in massive discussion transcripts and effectively assess learners'…

Effective collaboration and teamwork skills are critical in high-risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real-world scenarios, enabling students to safely improve their teamwork abilities. In such…

Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…

Understanding the processes in education, such as the student learning behavior within a specific course, is a key to continuous course improvement. In online learning systems, students' learning can be tracked and examined based on data collected by the systems themselves. However, it is non-trivial to decide how to extract the desired students'…

Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…

Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…

This volume presents the second edition of the "Communicative Orientation of Language Teaching (COLT) Observation Scheme." Since the book's original publication, COLT has become well established as a research instrument in L2 teaching and learning. This new edition brings COLT into the 21st century by introducing digital versions of the…

Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated…

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…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

The analysis of student questions can be used to improve the learning experience for both students and teachers. We investigated questions (N = 6457) asked before the class by first-year medicine/pharmacy students on an online platform, used by professors to prepare for Q&A sessions. Our long-term objectives are to help professors in…