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Knight, Simon; Buckingham Shum, Simon; Ryan, Philippa; Sándor, Ágnes; Wang, Xiaolong – International Journal of Artificial Intelligence in Education, 2018
Research into the teaching and assessment of student writing shows that many students find academic writing a challenge to learn, with legal writing no exception. Improving the availability and quality of timely formative feedback is an important aim. However, the time-consuming nature of assessing writing makes it impractical for instructors to…
Descriptors: Writing Evaluation, Natural Language Processing, Legal Education (Professions), Undergraduate Students
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Perin, Dolores; Lauterbach, Mark – International Journal of Artificial Intelligence in Education, 2018
The problem of poor writing skills at the postsecondary level is a large and troubling one. This study investigated the writing skills of low-skilled adults attending college developmental education courses by determining whether variables from an automated scoring system were predictive of human scores on writing quality rubrics. The human-scored…
Descriptors: College Students, Writing Evaluation, Writing Skills, Developmental Studies Programs
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Weston-Sementelli, Jennifer L.; Allen, Laura K.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2018
Source-based essays are evaluated both on the quality of the writing and the content appropriate interpretation and use of source material. Hence, composing a high-quality source-based essay (an essay written based on source material) relies on skills related to both reading (the sources) and writing (the essay) skills. As such, source-based…
Descriptors: Reading Comprehension, Writing Strategies, Writing Instruction, Essays
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Passonneau, Rebecca J.; Poddar, Ananya; Gite, Gaurav; Krivokapic, Alisa; Yang, Qian; Perin, Dolores – International Journal of Artificial Intelligence in Education, 2018
Development of reliable rubrics for educational intervention studies that address reading and writing skills is labor-intensive, and could benefit from an automated approach. We compare a main ideas rubric used in a successful writing intervention study to a highly reliable wise-crowd content assessment method developed to evaluate…
Descriptors: Computer Assisted Testing, Writing Evaluation, Content Analysis, Scoring Rubrics
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Vajjala, Sowmya – International Journal of Artificial Intelligence in Education, 2018
Automatic essay scoring (AES) refers to the process of scoring free text responses to given prompts, considering human grader scores as the gold standard. Writing such essays is an essential component of many language and aptitude exams. Hence, AES became an active and established area of research, and there are many proprietary systems used in…
Descriptors: Computer Software, Essays, Writing Evaluation, Scoring
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Goldberg, Benjamin; Amburn, Charles; Ragusa, Charlie; Chen, Dar-Wei – International Journal of Artificial Intelligence in Education, 2018
The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…
Descriptors: Psychomotor Skills, Intelligent Tutoring Systems, Program Validation, Models
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Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B. – International Journal of Artificial Intelligence in Education, 2018
The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…
Descriptors: Meta Analysis, Teaching Methods, Teamwork, Outcomes of Education
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Fletcher, J. D.; Sottilare, Robert A. – International Journal of Artificial Intelligence in Education, 2018
Teams and teamwork are ubiquitous in military and civilian organizations. Their importance to organizational success cannot be overstated. This article describes the relationship and effect of three concepts: Intelligent Tutoring Systems (ITSs), shared mental models, and teamwork. The nexus between these concepts is examined to determine its…
Descriptors: Teamwork, Teaching Methods, Intelligent Tutoring Systems, Schemata (Cognition)
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Gilbert, Stephen B.; Slavina, Anna; Dorneich, Michael C.; Sinatra, Anne M.; Bonner, Desmond; Johnston, Joan; Holub, Joseph; MacAllister, Anastacia; Winer, Eliot – International Journal of Artificial Intelligence in Education, 2018
With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of…
Descriptors: Tutors, Teamwork, Intelligent Tutoring Systems, Tutoring
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DeFalco, Jeanine A.; Rowe, Jonathan P.; Paquette, Luc; Georgoulas-Sherry, Vasiliki; Brawner, Keith; Mott, Bradford W.; Baker, Ryan S.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2018
Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences. Creating successful affective responses requires considerable effort both to detect student affect and to design appropriate responses to affect. Recent work has suggested that affect detection is more effective when both physical…
Descriptors: Psychological Patterns, Stress Variables, Educational Games, Intelligent Tutoring Systems
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Worsley, Marcelo; Blikstein, Paulo – International Journal of Artificial Intelligence in Education, 2018
This paper presents three multimodal learning analytic approaches from a hands-on learning activity. We use video, audio, gesture and bio-physiology data from a two-condition study (N = 20), to identify correlations between the multimodal data, experimental condition, and two learning outcomes: design quality and learning. The three approaches…
Descriptors: Multimedia Materials, Correlation, Outcomes of Education, Design
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Dermeval, Diego; Paiva, Ranilson; Bittencourt, Ig Ibert; Vassileva, Julita; Borges, Daniel – International Journal of Artificial Intelligence in Education, 2018
Authoring tools have been broadly used to design Intelligent Tutoring Systems (ITS). However, ITS community still lacks a current understanding of how authoring tools are used by non-programmer authors to design ITS. Hence, the objective of this work is to review how authoring tools have been supporting ITS design for non-programmer authors. In…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Software, Evidence
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Beemer, Joshua; Spoon, Kelly; He, Lingjun; Fan, Juanjuan; Levine, Richard A. – International Journal of Artificial Intelligence in Education, 2018
Student success efficacy studies are aimed at assessing instructional practices and learning environments by evaluating the success of and characterizing student subgroups that may benefit from such modalities. We propose an ensemble learning approach to perform these analytics tasks with specific focus on estimating individualized treatment…
Descriptors: Teaching Methods, Intervention, Experimental Groups, Control Groups
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McCarthy, Kathryn S.; Likens, Aaron D.; Johnson, Amy M.; Guerrero, Tricia A.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2018
Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing…
Descriptors: Metacognition, Difficulty Level, Prompting, Intelligent Tutoring Systems
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Vie, Jill-Jênn; Popineau, Fabrice; Bruillard, Éric; Bourda, Yolaine – International Journal of Artificial Intelligence in Education, 2018
In large-scale assessments such as the ones encountered in MOOCs, a lot of usage data is available because of the number of learners involved. Newcomers, that just arrive on a MOOC, have various backgrounds in terms of knowledge, but the platform hardly knows anything about them. Therefore, it is crucial to elicit their knowledge fast, in order to…
Descriptors: Automation, Test Construction, Measurement, Online Courses
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