Artificial Intelligence in the Classroom: The Impact of a Computer-Based Tutor on Teachers and Students

Schofield, Janet Ward; Evans-Rhodes, Debra; Huber, Brad R.

doi:10.1177/089443939000800104

Cited by 41 publications

(19 citation statements)

References 4 publications

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“…In addition to student learning from computer technology, both teachers and students report more time spent on task, increased motivation, and enhanced confidence (e.g., Schofield, Evans-Rhodes, & Huber, 1990). Furthermore, the potential added value of computer literacy should not be discounted (Kmitta & Davis, 2004).…”

Section: Educational Technology Goals and Benefitsmentioning

confidence: 99%

A Quasi-Experimental Evaluation of An On-Line Formative Assessment and Tutoring System

Koedinger

McLaughlin

Heffernan

2010

Journal of Educational Computing Research

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ASSISTments is a web-based math tutor designed to address the need for timely student assessment while simultaneously providing instruction, thereby avoiding lost instruction time that typically occurs during assessment. This article presents a quasi-experiment that evaluates whether ASSISTments use has an effect on improving middle school students' year-end test scores. The data was collected from 1240 seventh graders in three treatment schools and one comparison school. Post-test (7th grade year-end test) results indicate, after adjusting for the pre-test (6th grade year-end test), that students in the treatment schools significantly outperformed students in the comparison school and the difference was especially present for special education students. A usage analysis reveals that greater student use of ASSISTments is associated with greater learning consistent with the hypothesis that it is useful as a tutoring system. We also found evidence consistent with the hypothesis that teachers adapt their whole class instruction based on overall

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Section: Educational Technology Goals and Benefitsmentioning

confidence: 99%

A Quasi-Experimental Evaluation of An On-Line Formative Assessment and Tutoring System

Koedinger

McLaughlin

Heffernan

2010

Journal of Educational Computing Research

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“…Intelligent tutors for high school math tutors had also been used in smaller-scale experimental comparisons in schools (cf., Schofield et al 1990). So, it was definitely not the first experimental trial in schools.…”

Section: Q) Why Was This Work At the Time An Important Thing To Do mentioning

confidence: 99%

An Interview Reflection on “Intelligent Tutoring Goes to School in the Big City”

Koedinger

Aleven

2015

Int J Artif Intell Educ

209

198

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Our 1997 article in IJAIED reported on a study that showed that a new algebra curriculum with an embedded intelligent tutoring system (the Algebra Cognitive Tutor) dramatically enhanced high-school students' learning. The main motivation for the study was to demonstrate that intelligent tutors that have cognitive science research embedded in them could have real impact in schools. This study was one of the first large-scale classroom evaluations of the integrated use of an Intelligent Tutoring System (ITS) in high schools. A core challenge was figuring out how to embed this new technology into a curriculum and into the existing social context of schools. A key element of the study design was to include multiple kinds of assessments, including standardized test items and items measuring complex problem solving and use of representations. The results were powerful: BOn average the 470 students in experimental classes outperformed students in comparison classes by 15 % on standardized tests and 100 % on tests targeting the [course] objectives.^We suggested that the study was evidence Bthat laboratory tutoring systems can be scaled up and made to work, both technically and pedagogically, in real and unforgiving settings like urban high schools.^Since this study, many more classroom studies comparing instruction that includes an ITS against business as usual have been conducted, often showing advantages for the ITS-enhanced curricula. More rigorous randomized field trials are now more commonplace, but the approach of using multiple assessments in large-scale randomized field trials has not caught on. Cognitive task analysis will remain fundamental to the success of ITSs. A key remaining question for ITS is to find out how they can be used most effectively to support open-ended problem solving, either online or offline. Given all the recent excitement around Massive Open Online Courses (MOOCs), it is interesting to note that our field of

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“…Students' relation to the teacher changed as they moved from the classroom to the lab. The shift in their relationship paralleled the change in teacher-student relationships when geometry students shifted from whole class instruction to work on the GPTutor (Schofield, Evans-Rhodes, & Huber, 1989;1990).…”

Section: The Basis For Students' Preference For the Labmentioning

confidence: 98%

“…Just as the teachers of students using the GPTutors circulated and dealt with student's problems individually (Schofield, Evans-Rhodes, & Huber, 1989;1990), so too the computer science teachers went from student to student in the lab as the need arose. This occurred quite spontaneously since different students had problems with different parts of their programs.…”

Section: The Classroom and The Laboratorymentioning

confidence: 99%

See 1 more Smart Citation

A Tale of Two Settings: The Lab and the Classroom

Schofield¹

1991

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Artificial Intelligence in the Classroom: The Impact of a Computer-Based Tutor on Teachers and Students

Cited by 41 publications

References 4 publications

A Quasi-Experimental Evaluation of An On-Line Formative Assessment and Tutoring System

A Quasi-Experimental Evaluation of An On-Line Formative Assessment and Tutoring System

An Interview Reflection on “Intelligent Tutoring Goes to School in the Big City”

A Tale of Two Settings: The Lab and the Classroom

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