Modelling techniques for tutoring systems

Mitchell, Pru; Grogono, Peter

doi:10.1016/0360-1315(93)90070-y

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…For instance, Intelligent Tutoring of the Structure Strategy (ITSS) is a web‐based tutoring system which facilitates understanding of text by explicitly teaching learners how to follow the propositional structure of text by applying knowledge about text structures (Meyer et al , ; Meyer, Young, & Bartlett, ). There are also ITSs designed to help human tutors, rather than replacing them entirely (Danis et al , ; Mitchell & Grogono, ). Alphie's Alley is one such software program.…”

Section: Resultsmentioning

confidence: 99%

The effectiveness of intelligent tutoring systems on K‐12 students' reading comprehension: A meta‐analysis

Xu¹,

Wijekumar²,

Ramı́rez³

et al. 2019

Brit J Educational Tech

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This meta‐analysis examined the effectiveness of improving reading comprehension for students in K‐12 classrooms using intelligent tutoring systems (ITSs), a computer‐based learning environment that provides customizable and immediate feedback to the learner. Nineteen studies from 13 publications incorporating approximately 10 000 students were included in the final analysis; using robust variance estimation to account for statistical dependencies, the 19 studies yielded 88 effect size estimates. The meta‐analysis indicated that the overall random effect size of ITSs on reading comprehension was 0.60 (using a mix of standardized and researcher‐designed measures) with a 95% confidence interval 0.36 to 0.85 (p < 0.001). This review confirms previous studies comparing ITSs to human tutoring: ITSs produced a small effect size when compared to human tutoring (0.20, 0.02–0.38, p = 0.036, n = 21). All comparisons to human tutoring used standardized measures. This review also found that ITSs produced a larger effect size on reading comprehension when compared to traditional instruction (0.86) for mixed measures and (0.26) for standardized measures. These findings may be of interest to practitioners and policy makers seeking to improve reading comprehension using consistent and accessible ITSs. Recommendations for researchers include conducting studies to understand the difference between traditional and updated versions of ITSs and employing valid and reliable standardized tests and researcher‐designed measures.

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Section: Resultsmentioning

confidence: 99%

The effectiveness of intelligent tutoring systems on K‐12 students' reading comprehension: A meta‐analysis

Xu¹,

Wijekumar²,

Ramı́rez³

et al. 2019

Brit J Educational Tech

View full text Add to dashboard Cite

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“…Alphie's Alley contains a complex database that allows the computer to make "intelligent" decisions on interventions and strategies based on the performance of each student, both between and within sessions (Everson, 1995;Mitchell & Grogono, 1993). The computer analyzes a student's responses and provides to the tutor suggested templates of instruction for that student.…”

Section: Computer-assisted Tutoring: Alphie's Alleymentioning

confidence: 99%

Technology Infusion in Success for All: Reading Outcomes for First Graders

Chambers

Slavin

Madden

et al. 2008

The Elementary School Journal

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“…Although some task automation is included in Alphie's Alley as part of the support features, our discussions on artifi cial intelligence (based on Everson, 1995;Mandl & Lesgold, 1988;Mitchell & Grogono, 1993) concluded that adaptive branching was undesirable given the fact that we do not envisage the computer replacing a human tutor. Because our goal is to use the computer and the SFA tutor skills in concert for the progress of the child, we decided to enhance the computerized diagnostic and assessment activities toward a front-end complexity that will simplify the tutor's record-keeping and memory skills so his or her full attention can be devoted to the child.…”

Section: Electronic Performance Support Systems: a Framework For The mentioning

confidence: 99%