Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

Students often struggle with developing understanding from expository science texts. This study explored whether training students to engage in a POE (Predict-Observe-Explain) study strategy might be beneficial when learning from texts that introduce theories by describing experiments and empirical results, a common style in social science…

Predicting student problem-solving strategies is a complex problem but one that can significantly impact automated instruction systems since they can adapt or personalize the system to suit the learner. While for small datasets, learning experts may be able to manually analyze data to infer student strategies, for large datasets, this approach is…

Self-regulated learning (SRL) is an essential skill to achieve one's learning goals. This is particularly true for online learning environments (OLEs) where the support system is often limited compared to a traditional classroom setting. Likewise, existing research has found that learners often struggle to adapt their behaviour to the…

Problem solving is a key component of authentic scientific research and practice in organic chemistry. One factor that has been shown to have a major role in successful problem solving in a variety of disciplines is metacognitive regulation, defined as the control of one's thought processes through the use of planning, monitoring, and evaluation…

We analyse the predictive power of learning strategies for engineering students' performance in mathematics. Learning strategies play an important role in self-regulated learning. Based on a new learning strategy questionnaire that takes into account the specifics of mathematical learning at universities, we investigated what were the strategies…

This study examined how teachers support self-regulated learning (SRL) by examining reports of 15 potential practices and differentiated the use of these practices via teachers' SRL knowledge, beliefs, demographics, and student characteristics. Teachers (n = 112) responded to open-ended questions targeting SRL knowledge, beliefs, and practices and…

Task-relevant actions can facilitate mathematical thinking, even for complex topics, such as mathematical proof. We investigated whether such cognitive benefits also occur for action predictions. The action-cognition transduction (ACT) model posits a reciprocal relationship between movements and reasoning. Movements--imagined as well as real ones…

Path analysis is used to provide estimates of the magnitude and significance of hypothesized causal connections among sets of variables displayed using path diagrams. It is an extension of multiple regression analysis and holds strength as a methodology as it allows researchers to assess both direct and indirect effects of multiple independent…

Within the framework of Self-Determination Theory (SDT), basic psychological need satisfaction predicts quality of motivation which in turn predicts study efforts. Although studies focusing on interpersonal differences have repeatedly shown this sequence of relations, only a few have examined its stability at the intra-personal level. In this…

This study aims to better understand differences in the decision-making process behind study choices for higher education by investigating the presence of exploration profiles and then explore the explanatory base. To achieve this, we first identified different exploration profiles of students transitioning to higher education (n = 5660), and then…

Background: Students employ a variety of study strategies to learn and master content in their courses. Strategies vary widely in their effectiveness for promoting deep, long-term learning, yet most students use ineffective strategies frequently. Efforts to educate students about effective study strategies have revealed that knowledge about…

Predicting student performance in Massive Open Online Courses (MOOCs) is important to aid in retention efforts. Researchers have demonstrated that video watching features can be used to accurately predict student test performance on video quizzes employing neural networks to predict video test grades from viewing behavior including video searching…

Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…

School or academic achievement is a relevant topic of study, as it is evidence of the learning achieved by the student. This study aims to explore a model explaining academic achievement while testing the mediator role of learning strategies, study habits and study attitudes. Research design was correlational. 1712 Dominican students from 12 to 20…