Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…

Distance learning frees the learning process from spatial constraints. Each mode of distance learning, including synchronous and asynchronous learning, has disadvantages. In synchronous learning, students have network bandwidth and noise concerns, but in asynchronous learning, they have fewer opportunities for engagement, such as asking questions.…

Assessment and institutional research offices have too much data and too little time. Standard reporting often crowds out opportunities for innovative research. Fortunately, advancements in data science now offer a clear solution. It is equal parts technique and philosophy. The first and easiest step is to modernize data work. This column…

Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…

There are thousands of participants in different programming MOOCs (Massive Open Online Courses) which means thousands of solutions have to be assessed. As it is very time-consuming to assess that amount of solutions manually, using automated assessment is essential. Since task requirements must be strict for the solutions to be automatically…

Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…

The recommender system has gained research attention from education research communities mainly due to two main reasons: increasing needs for personalized learning and big data availability in the education sector. This paper presents a hybrid user-collaborative, rule-based filtering recommendation system for education context. User profiles are…

Our world has been transformed by technologies incorporating artificial intelligence (AI) within mass communication, employment, entertainment and many other aspects of our daily lives. However, within the domain of education, it seems that our ways of working and, particularly, assessing have hardly changed at all. We continue to prize…

2017 marked a century since the development and administration of the first large-scale group administered standardized test. Since that time, both the importance of testing and the technology of testing have advanced significantly. This paper traces the technological advances that have led to the large-scale administration of educational tests in…

This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods--including classical test theory, item response theory, and computer adaptive testing--and integrates them with multidimensional student models used by intelligent educational systems.…

The goal of this paper is to examine single variable real inequalities that arise as tutorial problems and to examine the extent to which current computer algebra systems (CAS) can (1) automatically solve such problems and (2) determine whether students' own answers to such problems are correct. We review how inequalities arise in contemporary…

For the last century, the quality of large-scale assessment in the United States has been undermined by narrow educational theory and hindered by limitations in technology. As a result, poor assessment practices have encouraged low-level instructional practices that disparately affect students from the most disadvantaged communities and schools.…

This article sets out to explore a shift in the sources of evidence-of-learning in the era of networked computing. One of the key features of recent developments has been popularly characterized as "big data". We begin by examining, in general terms, the frame of reference of contemporary debates on machine intelligence and the role of…

This report evaluates the construct coverage of the e-rater[R[ scoring engine. The matter of construct coverage depends on whether one defines writing skill, in terms of process or product. Originally, the e-rater engine consisted of a large set of components with a proven ability to predict human holistic scores. By organizing these capabilities…

A desirable characteristic for an e-learning system is to provide the learner the most appropriate information based on his requirements and preferences. This can be achieved by capturing and utilizing the learner model. Learner models can be extracted based on personality factors like learning styles, behavioral factors like user's browsing…