This article situates the potential for intellectual work to be renewed through an enriched engagement with the relationship between indigenous protocols and artificial intelligence (AI). It situates this through a dialectical storytelling of the contradictions that emerge from the relationships between humans and capitalist technologies, played…

Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…

Contemporary research that looks at self-regulated learning (SRL) as processes of learning events derived from trace data has attracted increasing interest over the past decade. However, limited research has been conducted that looks into the validity of trace-based measurement protocols. In order to fill this gap in the literature, we propose a…

Artificial intelligence (AI) technologies have the potential to reduce the workload for the second language (L2) teachers and test developers. We propose two AI distractor-generating methods for creating Chinese vocabulary items: semantic similarity and visual similarity. Semantic similarity refers to antonyms and synonyms, while visual similarity…

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Policy problems like "What should we do about global warming?" are ill-defined in large part because we do not agree on a system to represent them the way we agree Algebra problems should be represented by equations. As a first step toward building a policy deliberation tutor, we investigated: (a) whether causal diagrams help students learn to…

Purpose: To get beyond religious, philosophic, and political definitions of educatedness by going empirical. To redo Plato, in effect, by defining "the good" empirically. Background: This research was part of the Excellence Science (orthogonal disciplines) Research Project at the University of Chicago. That project redid Plato by…

Discusses intelligent tutoring systems (ITS), one application of artificial intelligence to computers used in education. Basic designs of ITSs are described; examples are given including PROUST, GREATERP, and the use of simulation with ITSs; protocol analysis is discussed; and 38 prototype ITSs are listed. (LRW)

A study examined in detail the initial encoding of worked-out examples of mechanics problems by "good" and "poor" students, and their subsequent reliance on examples during problem solving. The subjects, three males and five females, were selected from responses to a university campus advertisement. Six of them were working…

Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

This report discusses the importance of presenting qualitative, causally consistent models in the initial stages of learning so that students can gain an understanding of basic electrical circuit concepts and principles that builds on their preexisting ways of reasoning about physical phenomena, and it argues that tutoring environments must help…