Students are often encouraged to learn 'deeply' by abstracting generalizable principles from course content rather than memorizing details. So widespread is this perspective that Likert-style inventories are now routinely administered to students to quantify how much a given course or curriculum evokes deep learning. The predictive validity of…

Background: The Teacher-Student relationship (TSR) is instrumental for young children and adolescents' socio-emotional development and wellbeing as well as academic engagement and progress. Aims: The primary aim of this study was to test the psychometric properties, including reliability and factorial, convergent, and predictive validity, of the…

This study aimed to determine the relationship between the teaching efficacy of physical education teacher candidates and their teaching-learning conceptions and to determine the validity of the level of teaching efficacy predicting teaching-learning conceptions. The study group consisted of 433 teacher candidates studying in physical education…

This study presents empirical findings demonstrating predictive validities of noncognitive variables for mathematics achievement among primary and secondary school students from cross-country perspectives. Results based on TIMSS 2015 assessment showed that confidence was a moderately strong predictor of mathematics achievement in all TIMSS…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…

This study's objective is to determine if students who were unable to successfully complete a required sophomore level business software applications course encountered unique academic difficulties in that course, or if their difficulty signaled more general academic achievement problems in business. The study points to the importance of including…

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

The purpose of this study was to contribute to the academic discussion regarding the validity of Multiple Intelligences (MI) theory through focusing on the validity of an important construct embedded in the theory, that of congruence between instructional style and preferred MI style for optimal learning. Currently there is insufficient empirical…

The purpose of the present study was to investigate to what extent self-regulated learning (SRL) is context-dependent. The "Motivated Strategies for Learning Questionnaire" (MSLQ) was repeatedly administered to 155 first-year students at a Singaporean polytechnic--a general version of the MSLQ before students entered the polytechnic and…

This paper draws on the concept and process of deeper learning, namely the U theory (Senge, Scharmer, Jaworski, & Flowers, 2004a). As a driver to get a deeper exploration of organisational change process, the theory of U goes beyond the interpersonal aspects of learning, instead focusing on a deeper personal generative learning that emphasizes…

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…