Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…

The Future Skills Report about the future of learning and higher Education (Ehlers & Kellermann, 2019) defines a variety of skills in which the active learner plays a central role. Starting from this perspective, our idea is to promote future skills with a digital data-driven study assistant for. As a theoretical foundation research about…

Scoring of teachers' noticing responses is typically burdened with rater bias and reliance upon interrater consensus. The authors sought to make the scoring process more objective, equitable, and generalizable. The development process began with a description of response characteristics for each professional noticing component disconnected from…

The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…

Although badges are among the most-used game elements in gamified education, studies about their optimal features to motivate learning are scarce. How should a badge be designed to represent an incentive for a specific goal like optimal exam preparation? This study examines usage data of a higher education learning app to determine whether the…

Improving the pedagogical effectiveness of programming training platforms is a hot topic that requires the construction of fine and exploitable representations of learners' programs. This article presents a new approach for learning program embeddings. Starting from the hypothesis that the function of a program, but also its "style", can…

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…

Transactive discussion during collaborative learning is crucial for building on each other's reasoning and developing problem solving strategies. In a tabletop collaborative learning activity, student actions on the interface can drive their thinking and be used to ground discussions, thus affecting their problem-solving performance and learning.…

Personalized learning stems from the idea that students benefit from instructional material tailored to their needs. Many online learning platforms purport to implement some form of personalized learning, often through on-demand tutoring or self-paced instruction, but to our knowledge none have a way to automatically explore for specific…