Feedback is a crucial component of student learning. As advancements in technology have enabled the adoption of digital learning environments with assessment capabilities, the frequency, delivery format, and timeliness of feedback derived from educational assessments have also changed progressively. Advanced technologies powered by Artificial…

A model that maps the requisite skills, or knowledge components, to the contents of an online course is necessary to implement many adaptive learning technologies. However, developing a skill model and tagging courseware contents with individual skills can be expensive and error prone. We propose a technology to automatically identify latent…

Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…

To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not…

We present the results of an ongoing collaboration between computer science and psychology researchers that employs Natural Language Processing (NLP) methods to examine the trajectory of semantic space used during group idea generation sessions. Specifically, we track and estimate the region of semantic space being used and the degree to which new…

Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…

Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…

The launch of ChatGPT has been revolutionary. This AI chatbot can produce conversations which are indistinguishable from that of humans. This exploratory qualitative study is foregrounded in a constructivist-interpretative perspective. The principal objective of this paper is to explore the views of academics on ChatGPT as an AI-based learning…

The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of "adaptive textbooks" that can help readers to learn better through adapting to the readers' learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by…

Among all the learning resources within MOOCs such as video lectures and homework, the discussion forum stood out as a valuable platform for students' learning through knowledge exchange. However, peer interactions on MOOC discussion forums are scarce. The lack of interactions among MOOC learners can yield negative effects on students' learning,…

In this digital age, there is an abundance of online educational materials in public and proprietary platforms. To allow effective retrieval of educational resources, it is a necessity to build keyword-based search engines over these collections. In modern Web search engines, high-quality rankings are obtained by applying machine learning…

We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

Today, there is a vast amount of online material for learners. However, due to the lack of prerequisite information needed to master them, a lot of time is spent in identifying the right learning content for mastering these concepts. A system that captures underlying prerequisites needed for learning different concepts can help improve the quality…

From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial…