Work In Progress: The Effect of Partially-Completed Worked Examples Applied to Statics

John Martin; Anna Martin

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Conference: 2017 ASEE Annual Conference & Exposition
Location: Columbus, Ohio
Publication Date: June 24, 2017
Start Date: June 24, 2017
End Date: June 28, 2017
Conference Session: Curricular Innovations 1
Tagged Division: Educational Research and Methods
Page Count: 6
DOI: 10.18260/1-2--29181
Permanent URL: https://strategy.asee.org/29181
Download Count: 926

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Paper Authors

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John Martin Youngstown State University

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John Martin is an Assistant Professor of Mechanical Engineering Technology at Youngstown State University. John has seven years of mechanical engineering experience.

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Anna Martin Kent State University

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Anna Martin is a doctoral student of Educational Psychology and Instructional Technology at Kent State University and a high-school social studies teacher at Canfield High School with 9 years of experience.

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Abstract

Traditionally, instructional strategies used for teaching engineering subjects revolve around a scaffolded type framework, where problems are solved in-class by the instructor whom provides guidance to students that are simultaneously engaging in the problem solving with the instructor. This type of learning strategy is based off of a guided problem-solving approach. After a number of problems are solved in this manner the next step is usually to assign problems for the students to solve entirely on their own, taking away all the instructor support from the problem-solving approach. Research suggests that entirely removing all guidance too soon generally results in a situation where student learning must then rely on randomness. This is where the learning process is accomplished by randomly combining elements of information and then determining which combinations are effective (Sweller 2004), which is very inefficient.

This type of learning technique is very common within engineering subjects, as well as many other subjects and is based off of what is sometimes referred to as discovery learning (Bruner 1961). Research has suggested that making use of partially-completed worked examples can reduce cognitive load by decreasing the burden on working memory (Carrol 1994, etc.), in turn leaving more memory capacity to acquire knowledge. In partially-completed worked-examples learners are given a problem where certain portions of that problem are missing and they are required to fill in the missing steps. Implementing this instructional strategy can serve as a bridge between fully guided problem-solving and completely unguided problem solving. Adding the use of partially-completed worked examples to fill the gap between worked examples and independent problem solving has proven to be very effective in prior research (Paas 1992).

This study will examine the effectiveness of implementing partially-completed worked examples when directly applied to the field of Statics. This study will specifically examine whether or not the use of partially-completed worked examples create a more efficient and complete learning process when learning Statics.

We will utilize a quantitative quasi-experimental pretest-posttest study to gain a better understanding of the effects of partially-completed worked examples of Statics problems on student learning. Students within an engineering Statics course will be divided into two groups, where the first group will be given partially-completed worked examples along with traditional problems, where they are to solve the partially completed problems first and then the traditional problems afterwards. The second group will be given only traditional problems to solve. Additionally, a subjective measure of cognitive load will be used to quantify between group cognitive loads, while a posttest will measure student learning of the topic in general. The instructional strategy will serve as the independent variable consisting of two groups, while the engineering concept knowledge of Statics, along with the subjective cognitive load scores will serve as the dependent variables to be measured using multivariate analysis of variance (MANOVA).

Firm student understanding of fundamental courses such as Statics is crucial for their success in subsequent courses, and is also vital in providing solid background knowledge to appropriately comprehend more advanced topics. In order to maximize the learning process a clearer understanding of how the role of guidance during problem solving impacts student learning is necessary. This study hopes to shed light on the way in which instructional delivery impacts learning of engineering concepts.

References Bruner, J. (1961). The act of discovery, Harvard Educational Review, 31: 21-32.

Carrol, W. (1994). Using worked examples as an instructional support in the algebra classroom, Journal of Educational Psychology, 86: 360-367.

Paas, F. (1992). Training strategies for attaining transfer of problem-solving skills in statistics: A Cognitive-Load approach, Journal of Educational Psychology, 84: 429-434.

Sweller, J. (2004). Instructional Design Consequences of an Analogy between Evolution by Natural Selection and Human Cognitive Architecture, Instructional Science, 32: 9-31.

Citation
Format

Martin, J., & Martin, A. (2017, June), Work In Progress: The Effect of Partially-Completed Worked Examples Applied to Statics Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--29181

TY - CPAPER
AB - Traditionally, instructional strategies used for teaching engineering subjects revolve around a scaffolded type framework, where problems are solved in-class by the instructor whom provides guidance to students that are simultaneously engaging in the problem solving with the instructor. This type of learning strategy is based off of a guided problem-solving approach. After a number of problems are solved in this manner the next step is usually to assign problems for the students to solve entirely on their own, taking away all the instructor support from the problem-solving approach. Research suggests that entirely removing all guidance too soon generally results in a situation where student learning must then rely on randomness. This is where the learning process is accomplished by randomly combining elements of information and then determining which combinations are effective (Sweller 2004), which is very inefficient.

This type of learning technique is very common within engineering subjects, as well as many other subjects and is based off of what is sometimes referred to as discovery learning (Bruner 1961). Research has suggested that making use of partially-completed worked examples can reduce cognitive load by decreasing the burden on working memory (Carrol 1994, etc.), in turn leaving more memory capacity to acquire knowledge. In partially-completed worked-examples learners are given a problem where certain portions of that problem are missing and they are required to fill in the missing steps. Implementing this instructional strategy can serve as a bridge between fully guided problem-solving and completely unguided problem solving. Adding the use of partially-completed worked examples to fill the gap between worked examples and independent problem solving has proven to be very effective in prior research (Paas 1992).

This study will examine the effectiveness of implementing partially-completed worked examples when directly applied to the field of Statics. This study will specifically examine whether or not the use of partially-completed worked examples create a more efficient and complete learning process when learning Statics.

We will utilize a quantitative quasi-experimental pretest-posttest study to gain a better understanding of the effects of partially-completed worked examples of Statics problems on student learning. Students within an engineering Statics course will be divided into two groups, where the first group will be given partially-completed worked examples along with traditional problems, where they are to solve the partially completed problems first and then the traditional problems afterwards. The second group will be given only traditional problems to solve. Additionally, a subjective measure of cognitive load will be used to quantify between group cognitive loads, while a posttest will measure student learning of the topic in general. The instructional strategy will serve as the independent variable consisting of two groups, while the engineering concept knowledge of Statics, along with the subjective cognitive load scores will serve as the dependent variables to be measured using multivariate analysis of variance (MANOVA).

Firm student understanding of fundamental courses such as Statics is crucial for their success in subsequent courses, and is also vital in providing solid background knowledge to appropriately comprehend more advanced topics. In order to maximize the learning process a clearer understanding of how the role of guidance during problem solving impacts student learning is necessary. This study hopes to shed light on the way in which instructional delivery impacts learning of engineering concepts.

References
Bruner, J. (1961). The act of discovery, Harvard Educational Review, 31: 21-32.

Carrol, W. (1994). Using worked examples as an instructional support in the algebra classroom, Journal of Educational Psychology, 86: 360-367.

Paas, F. (1992). Training strategies for attaining transfer of problem-solving skills in statistics: A Cognitive-Load approach, Journal of Educational Psychology, 84: 429-434.

Sweller, J. (2004). Instructional Design Consequences of an Analogy between Evolution by Natural Selection and Human Cognitive Architecture, Instructional Science, 32: 9-31.

AU - John Martin
AU - Anna Martin
CY - Columbus, Ohio
DA - 2017/06/24
PB - ASEE Conferences
TI - Work In Progress: The Effect of Partially-Completed Worked Examples Applied to Statics
UR - https://strategy.asee.org/29181
DO - 10.18260/1-2--29181
ER -