Intelligent diagnostic problem solving tutor: an experimental evaluation

Vasandani, V.; Govindaraj, T.

doi:10.1109/icsmc.1991.169944

Cited by 8 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the students who were more adaptive and generated an incorrect hypothesis were able to solve the simple problem quicker than their more innovative counterparts. Overall, these findings align with previous research suggesting those who generate accurate hypotheses are able to make better and quicker decisions when solving problems (Johnson, 1989;Vasandani & Govindaraj, 1991).…”

Section: Resultssupporting

confidence: 80%

See 1 more Smart Citation

Determining the Effects of Cognitive Style, Problem Complexity, and Hypothesis Generation on the Problem Solving Ability of School-Based Agricultural Education Students

Blackburn¹,

Robinson²

2016

JAE

View full text Add to dashboard Cite

show abstract

Section: Resultssupporting

confidence: 80%

“…If the hypothesis is disconfirmed, the troubleshooter cycles back to the first phase of the model and generates a new hypothesis to evaluate (see Figure 2). More successful troubleshooters are able to generate accurate hypotheses to solve problems quickly (Vasandani & Govindaraj, 1991).…”

Section: Conceptual Framementioning

confidence: 99%

Determining the Effects of Cognitive Style, Problem Complexity, and Hypothesis Generation on the Problem Solving Ability of School-Based Agricultural Education Students

Blackburn¹,

Robinson²

2016

JAE

View full text Add to dashboard Cite

show abstract

“…If the hypothesis is disconfirmed, the troubleshooter cycles back to the first phase of the model and generates a new hypothesis to evaluate (Johnson, 1989). The ability to generate accurate hypotheses quickly is a characteristic of successful troubleshooters (Vasandani & Govindaraj, 1991).…”

Section: Conceptual Frameworkmentioning

confidence: 99%

An Investigation of Factors that Influence the Hypothesis Generation Ability of Students in School-Based Agricultural Education Programs when Troubleshooting Small Gasline Engines

Blackburn¹,

Robinson²

2017

JAE

View full text Add to dashboard Cite

The purpose of this study was to determine if selected factors influenced the ability of students in school-based agricultural education programs to generate a correct hypothesis when troubleshooting small gasoline engines. Variables of interest included students' cognitive style, age, GPA, and content knowledge in small gasoline engines. Kirton's Adaption-Innovation Inventory was employed to assess cognitive style and a researcher developed criterion-referenced test was utilized to determine small gasoline content knowledge. Students were assigned randomly, by cognitive style, to generate a hypothesis for either a simple or complex small gasoline engine problem. A similar number of students were able to correctly hypothesize the fault in their assigned engine regardless of cognitive style. However, differences were noted between the more adaptive and more innovative students. A binary logistic regression revealed that as cognitive style score increased, the odds of generating a correct hypothesis decreased. Additionally, older students were more likely to generate an incorrect hypothesis. Teachers should encourage students to hypothesize when engaged in problem solving activities, but should be aware of individual differences such as cognitive style.

show abstract

“…Specifically, Johnson et al presented MITT Writer, an authoring environment for building intelligent tutoring systems for computer courses, which represented a practical application of AI in technical training [9]. In the same year, Vasandani et al developed an intelligent tutoring system that helps to organize system knowledge and operational information to enhance operator performance [18], [19]. Meanwhile, Gonzalez and Ingraham designed an intelligent tutoring system, which is capable of automatically determining exercise progression and remediation during a training session according to past student performance [2].…”

Section: Reviews Of Pertinent Literaturementioning

confidence: 99%

On the development of a cooperative tutoring environment on computer networks

Hwang

2002

IEEE Trans. Syst., Man, Cybern. C

View full text Add to dashboard Cite

In developing a tutoring system, one of the most difficult tasks is to collect tutoring knowledge from multiple educators, especially courses in which the contents change frequently, due to the advent of new technologies. In this paper, we propose a webbased intelligent tutoring strategy construction system, which is able to elicit, analyze, and integrate tutoring knowledge from multiple educators systematically. Experiments on two courses have been performed to evaluate the time, completeness, and accuracy improvement in constructing tutoring knowledge bases with our approach. According to the experimental results, it can be inferred that for most cases, our approach achieves desirable performances.

show abstract

Intelligent diagnostic problem solving tutor: an experimental evaluation

Cited by 8 publications

References 4 publications

Determining the Effects of Cognitive Style, Problem Complexity, and Hypothesis Generation on the Problem Solving Ability of School-Based Agricultural Education Students

Determining the Effects of Cognitive Style, Problem Complexity, and Hypothesis Generation on the Problem Solving Ability of School-Based Agricultural Education Students

An Investigation of Factors that Influence the Hypothesis Generation Ability of Students in School-Based Agricultural Education Programs when Troubleshooting Small Gasline Engines

On the development of a cooperative tutoring environment on computer networks

Contact Info

Product

Resources

About