Problem-solving on a computer-based teletype

1969 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Patrick Suppes ◽  
Elizabeth F. Loftus ◽  
Max Jerman
Keyword(s):  
Problem Solving ◽  
Computer Based

The Genetics Lab - A new computer-based problem solving scenario to assess intelligence

2011 ◽  
Author(s):  
Philipp Sonnleitner ◽  
Martin Brunner ◽  
Ulrich Keller ◽  
Romain Martin ◽  
Thibaud Latour
Keyword(s):  
Problem Solving ◽  
Computer Based

Computer-based Information Search and Ill-Defined Problem Solving

2002 ◽  
Author(s):  
Jody J. Illies ◽  
Jennifer A. Nies ◽  
Roni Reiter-Palmon
Keyword(s):  
Problem Solving ◽  
Information Search ◽  
Computer Based

Perspectives on Computer-Based Assessment of Problem Solving

2004 ◽  
Author(s):  
Harold O'Neil ◽  
San-Hui Chuang
Keyword(s):  
Problem Solving ◽  
Computer Based

scholarly journals The time on task effect in reading and problem solving is moderated by task difficulty and skill: Insights from a computer-based large-scale assessment.

2014 ◽  
Vol 106 (3) ◽  
pp. 608-626 ◽  
Author(s):  
Frank Goldhammer ◽  
Johannes Naumann ◽  
Annette Stelter ◽  
Krisztina Tóth ◽  
Heiko Rölke ◽  
...  
Keyword(s):  
Problem Solving ◽  
Task Difficulty ◽  
Large Scale ◽  
Time On Task ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Task Effect ◽  
Computer Based

Learning by Doing via Game Making

2011 ◽  
pp. 1354-1366
Author(s):  
Jae Yeob Jung ◽  
Hyung Sung Park
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Learning Styles ◽  
Learning Community ◽  
Knowledge Construction ◽  
Game Design ◽  
Higher Order Thinking ◽  
Learning By Doing ◽  
Computer Based ◽  
Interactive Simulations

The purpose of this chapter is to explore how learning, by making games, can provide opportunities for higher-order thinking such as problem solving, decision-making, and knowledge construction in children. As the game design process involves students drawing on multiple intelligences, it often provides students who are typically not successful in school with a chance to see themselves as capable members of the classroom learning community. In the classroom, computer-based game-making activities give students the opportunity to create lively interactive simulations for any subject, for any grade level, and can be used by students with a wide variety of learning styles. Game making can be used as an alternative way for students to communicate information and demonstrate their knowledge and understanding.

Computer-based simulations and clinical problem-solving

1984 ◽  
Vol 9 (3-4) ◽  
pp. 277-279 ◽  
Author(s):  
Octo Barnett
Keyword(s):  
Problem Solving ◽  
Clinical Problem ◽  
Clinical Problem Solving ◽  
Computer Based

Estimating student ability and problem difficulty using item response theory (IRT) and TrueSkill

2019 ◽  
Vol 47 (2) ◽  
pp. 67-75 ◽  
Author(s):  
Youngjin Lee
Keyword(s):  
Data Mining ◽  
Item Response Theory ◽  
Problem Solving ◽  
Learning Environment ◽  
Item Response ◽  
Predictive Power ◽  
Response Theory ◽  
Content Type ◽  
Computer Based Learning ◽  
Computer Based

Purpose The purpose of this paper is to investigate an efficient means of estimating the ability of students solving problems in the computer-based learning environment. Design/methodology/approach Item response theory (IRT) and TrueSkill were applied to simulated and real problem solving data to estimate the ability of students solving homework problems in the massive open online course (MOOC). Based on the estimated ability, data mining models predicting whether students can correctly solve homework and quiz problems in the MOOC were developed. The predictive power of IRT- and TrueSkill-based data mining models was compared in terms of Area Under the receiver operating characteristic Curve. Findings The correlation between students’ ability estimated from IRT and TrueSkill was strong. In addition, IRT- and TrueSkill-based data mining models showed a comparable predictive power when the data included a large number of students. While IRT failed to estimate students’ ability and could not predict their problem solving performance when the data included a small number of students, TrueSkill did not experience such problems. Originality/value Estimating students’ ability is critical to determine the most appropriate time for providing instructional scaffolding in the computer-based learning environment. The findings of this study suggest that TrueSkill can be an efficient means for estimating the ability of students solving problems in the computer-based learning environment regardless of the number of students.

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