Titlebook: Artificial Intelligence in Education; 22nd International C Ido Roll,Danielle McNamara,Vania Dimitrova Conference proceedings 2021 Springer

Fortuitous

RepairNet: Contextual Sequence-to-Sequence Network for Automated Program Repair repair such errors can be a useful aid to the developers for their productivity. In this work, we propose a deep generative model, RepairNet, that automatically repairs programs that fail at compile time. RepairNet is based on sequence-to-sequence modeling and uses both code and error messages to r

debouch

CARE

A Systematic Review of Data-Driven Approaches to Item Difficulty Predictionan determine items and tests’ overall quality. Therefore, . is extremely important in any pedagogical learning environment. Data-driven approaches to item difficulty prediction are gaining more and more prominence, as demonstrated by the recent literature. In this paper, we provide a systematic revi

易彎曲

虛度

Affect-Targeted Interviews for Understanding Student Frustrationrceptions about the learning activity drive their experience of frustration and their subsequent choices during learning. In this paper, we adopt a mixed-methods approach, using automated detectors of affect to signal classroom researchers to interview a specific student at a specific time. We hand-

ethnology

Explainable Recommendations in a Personalized Programming Practice Systemnalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explainable recommendations was assessed in a semester-long classroom study. The paper analyses the observ

螢火蟲

Multilingual Age of Exposureore creating more complex models of assessing text difficulty, the basic building block of a text consists of words and, inherently, its overall difficulty is greatly influenced by the complexity of underlying words. One approach is to measure a word’s Age of Acquisition (AoA), an estimate of the av

使高興

不理會

outskirts

Adaptively Scaffolding Cognitive Engagement with Batch Constrained Deep Q-Networksh a learning activity in terms of four different engagement modes—Interactive, Constructive, Active, and Passive—and it predicts that increased cognitive engagement will yield improved learning. However, a key open question is how best to translate the ICAP theory into the design of adaptive scaffol