Feedback Preferences of Students Learning in a Blended Environment: Worked Examples, Tutored and Untutored Problem-Solving

2020 ◽  
pp. 51-70
Author(s):  
Dirk T. Tempelaar ◽  
Bart Rienties ◽  
Quan Nguyen
Keyword(s):  
Problem Solving ◽  
Worked Examples ◽  
Feedback Preferences

Complex Problem Solving and Worked Examples

2009 ◽  
Vol 23 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Florian Schmidt-Weigand ◽  
Martin Hänze ◽  
Rita Wodzinski
Keyword(s):  
Problem Solving ◽  
Cognitive Load ◽  
Learning Experience ◽  
Worked Examples ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Strategic Learning ◽  
Learning Behavior ◽  
Worked Example ◽  
8Th Grade

How can worked examples be enhanced to promote complex problem solving? N = 92 students of the 8th grade attended in pairs to a physics problem. Problem solving was supported by (a) a worked example given as a whole, (b) a worked example presented incrementally (i.e. only one solution step at a time), or (c) a worked example presented incrementally and accompanied by strategic prompts. In groups (b) and (c) students self-regulated when to attend to the next solution step. In group (c) each solution step was preceded by a prompt that suggested strategic learning behavior (e.g. note taking, sketching, communicating with the learning partner, etc.). Prompts and solution steps were given on separate sheets. The study revealed that incremental presentation lead to a better learning experience (higher feeling of competence, lower cognitive load) compared to a conventional presentation of the worked example. However, only if additional strategic learning behavior was prompted, students remembered the solution more correctly and reproduced more solution steps.

scholarly journals A Test of the Testing Effect: Acquiring Problem-Solving Skills From Worked Examples

2012 ◽  
Vol 36 (8) ◽  
pp. 1532-1541 ◽  
Author(s):  
Tamara van Gog ◽  
Liesbeth Kester
Keyword(s):  
Problem Solving ◽  
Testing Effect ◽  
Worked Examples ◽  
Problem Solving Skills

Automated generators of examples and problems for studying computer algorithms

2019 ◽  
Vol 16 (3) ◽  
pp. 204-218
Author(s):  
Andrew Kwok-Fai Lui ◽  
Maria Hiu Man Poon ◽  
Raymond Man Hong Wong
Keyword(s):  
Problem Solving ◽  
Operating Systems ◽  
Worked Examples ◽  
Computer Algorithms ◽  
Learning Context ◽  
Content Type ◽  
Self Regulated Learning ◽  
Need Support ◽  
Unlimited Supply ◽  
Based Instruction

Purpose The purpose of this study is to investigate students’ decisions in example-based instruction within a novel self-regulated learning context. The novelty was the use of automated generators of worked examples and problem-solving exercises instead of a few handcrafted ones. According to the cognitive load theory, when students are in control of their learning, they demonstrate different preferences in selecting worked examples or problem solving exercises for maximizing their learning. An unlimited supply of examples and exercises, however, offers unprecedented degree of flexibility that should alter the decisions of students in scheduling the instruction. Design/methodology/approach ASolver, an online learning environment augmented with such generators for studying computer algorithms in an operating systems course, was developed as the experimental platform. Students’ decisions related to choosing worked examples or problem-solving exercises were logged and analyzed. Findings Results show that students had a tendency to attempt many exercises and examples, especially when performance measurement events were impending. Strong students had greater appetite for both exercises and examples than weak students, and they were found to be more adventurous and less bothered by scaffolding. On the other hand, weak students were found to be more timid or unmotivated. They need support in the form of procedural scaffolding to guide the learning. Originality/value This study was one of the first to introduce automated example generators for studying an operating systems course and investigate students’ behaviors in such learning environments.

Chemistry in Quantitative Language

2009 ◽  
Author(s):  
Christopher O. Oriakhi
Keyword(s):  
General Chemistry ◽  
Problem Solving ◽  
Worked Examples ◽  
First Year ◽  
Key Concepts

Problem-solving is one of the most challenging aspects students encounter in general chemistry courses leading to frustration and failure. Consequently, many students become less motivated to take additional chemistry courses after the first year. This book deals with calculations in general chemistry and its primary goal is to prevent frustration by providing students with innovative, intuitive, and systematic strategies to problem-solving in chemistry. The material addresses this issue by providing several sample problems with carefully explained step-by-step solutions for each concept. Key concepts, basic theories, and equations are provided and worked examples are selected to reflect possible ways problems could be presented to students.

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