Data science is becoming a mainstay in research. Despite this, very few STEM graduates matriculate with basic formal training in programming. The current lesson plan was developed to introduce undergraduates studying chemistry or biology to chemoinformatics and data science in medicinal chemistry. The objective of this lesson plan is to introduce…

The integration of artificial intelligence (AI) and biotechnology, whilst in its infancy, presents significant opportunities and risks, and proactive policy is needed to manage these emerging technologies. Whilst AI continues to have significant and broad impact, its relevance and complexity magnify when integrated with other emerging…

Assessing student knowledge based on their writing using traditional qualitative methods is time-consuming. To improve speed and consistency of text analysis, we present our mixed methods development of a machine learning predictive model to analyze student writing. Our approach involves two stages: first an exploratory sequential design, and…

Purpose: In November 2022, the commercial company, OpenAI, launched ChatGPT. Since then, university students have rapidly become regular users of this artificial intelligence (AI) platform. One reason for this is the powerful capability of this generative AI tool to produce textual content, which in many cases, is almost indistinguishable from…

In recent years, modern technologies have enabled the collection of exponentially larger quantities of data in the biomedical domain and elsewhere. In particular, the advent of single-cell genomics has allowed for the collection of datasets containing hundreds of thousands of cells measured in tens of thousands of dimensions. This rapid expansion…

Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners' emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions…

This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal…

High levels of attrition characterize undergraduate science courses in the USA. Predictive analytics research seeks to build models that identify at-risk students and suggest interventions that enhance student success. This study examines whether incorporating a novel assessment type (concept inventories [CI]) and using machine learning (ML)…

Theatrical performance constitutes a complicated way for students to express and to communicate with each other, since it targets both various artistic and educational goals. Even though it constitutes a top moment of students' expression, several students do not feel comfortable when participating in such cultural activities, as performance…

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…

Rapid developments in educational technology in higher education are intended to make learning more engaging and effective. At the same time, cognitive load theory stresses limitations of human cognitive architecture and urges educational developers to design learning tools that optimise learners' mental capacities. In a 2-month study we…

One of the core practices of science is constructing scientific explanations. However, numerous studies have shown that constructing scientific explanations poses significant challenges to students. Proper assessment of scientific explanations is costly and time-consuming, and teachers often do not have a clear definition of the educational goals…

Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…

The advent of artificial intelligence (AI)-powered language models presents new opportunities and challenges in education. By teaching students how to craft prompts that elicit insightful responses, faculty can scaffold activities where AI acts as a supplemental resource to amplify critical thinking and support student learning. Ongoing dialogue…

The pervasive use of distributional semantic models or word embeddings for both cognitive modeling and practical application is because of their remarkable ability to represent the meanings of words. However, relatively little effort has been made to explore what types of information are encoded in distributional word vectors. Knowing the internal…