Decision based learning for a sophomore level thermodynamics course.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Decision based learning for a sophomore level thermodynamics course.
Συγγραφείς: Hagge, Matthew, Amin-Naseri, Mostafa, Gilbert, Stephen B., Jackman, John, Guo, Enruo, Starns, Gloria, Faidley, LeAnn E.
Πηγή: Proceedings of the ASEE Annual Conference & Exposition; 2015, p1-17, 17p
Θεματικοί όροι: Engineering education, Thermodynamics, Physical & theoretical chemistry, Service learning, Problem solving
Περίληψη: To meet the challenges of today's engineers, educators need to better understand and utilize teaching methods. These challenges and possible solutions are explored in Felder et. al. In this paper, decision based learning (DBL) is presented as a new pedagogy in an attempt to address some of these challenges. In decision based learning, a student is given a problem that they have never seen before. The student is asked to make a set of instructor decisions. When the student is unable to make a decision correctly, the instructor attempts to improve student understanding. This process continues until the student is able to solve the problem. While DBL shares characteristics of existing methods, it is unique in formulating sets of general to specific decisions. The instructor decision sets, student responses, and instructor feedback can easily be shared by instructors of different experience level. A long term goal of DBL is to allow students to solve novel and complex problems with minimal instructor support. In this tutor, students were asked to draw a T-v phase diagram for a refrigeration cycle they had never seen before. At any point in the drawing process, students could submit their work to receive feedback. Upon submission, the tutor evaluated the student drawing to determine the most general/important understanding for which the student needed help. Rather than showing the correct answer, the tutor asked additional questions designed to assess the student's understanding. The tutor's response was contingent on the student's answers, potentially resulting in further assessments, instructional material, or returning to the problem at hand. The goal was to improve the student's understanding to the point where he or she could make a decision correctly. The decision making would, in turn, advance the student toward a correct solution. Students were asked to work at least 40 minutes on the activity. Students completed a pre-tutor test and a post-tutor test to determine the impact of the tutor in furthering students' understanding regarding (P,T,v) property relationships for thermodynamic components. A significant amount of learning was demonstrated using DBL as suggested by a Cohen's d=1.77 for 88 students, where d>0.8 shows a large effect [4]. The pre-test results indicate that, on average, only 25% of students were able to identify all three relations for components prior to the tutor activity. Liquid gas separator, evaporator and condenser were the components that were most misunderstood by students. The post-activity test showed significant learning for component relations. As an example, 58% of the students had a misconception about pressure for heat exchangers. This was reduced to 18% using a single activity. More detailed analysis investigated how students learned using this activity. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the ASEE Annual Conference & Exposition is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: To meet the challenges of today's engineers, educators need to better understand and utilize teaching methods. These challenges and possible solutions are explored in Felder et. al. In this paper, decision based learning (DBL) is presented as a new pedagogy in an attempt to address some of these challenges. In decision based learning, a student is given a problem that they have never seen before. The student is asked to make a set of instructor decisions. When the student is unable to make a decision correctly, the instructor attempts to improve student understanding. This process continues until the student is able to solve the problem. While DBL shares characteristics of existing methods, it is unique in formulating sets of general to specific decisions. The instructor decision sets, student responses, and instructor feedback can easily be shared by instructors of different experience level. A long term goal of DBL is to allow students to solve novel and complex problems with minimal instructor support. In this tutor, students were asked to draw a T-v phase diagram for a refrigeration cycle they had never seen before. At any point in the drawing process, students could submit their work to receive feedback. Upon submission, the tutor evaluated the student drawing to determine the most general/important understanding for which the student needed help. Rather than showing the correct answer, the tutor asked additional questions designed to assess the student's understanding. The tutor's response was contingent on the student's answers, potentially resulting in further assessments, instructional material, or returning to the problem at hand. The goal was to improve the student's understanding to the point where he or she could make a decision correctly. The decision making would, in turn, advance the student toward a correct solution. Students were asked to work at least 40 minutes on the activity. Students completed a pre-tutor test and a post-tutor test to determine the impact of the tutor in furthering students' understanding regarding (P,T,v) property relationships for thermodynamic components. A significant amount of learning was demonstrated using DBL as suggested by a Cohen's d=1.77 for 88 students, where d>0.8 shows a large effect [4]. The pre-test results indicate that, on average, only 25% of students were able to identify all three relations for components prior to the tutor activity. Liquid gas separator, evaporator and condenser were the components that were most misunderstood by students. The post-activity test showed significant learning for component relations. As an example, 58% of the students had a misconception about pressure for heat exchangers. This was reduced to 18% using a single activity. More detailed analysis investigated how students learned using this activity. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Proceedings of the ASEE Annual Conference & Exposition is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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    Subjects:
      – SubjectFull: Engineering education
        Type: general
      – SubjectFull: Thermodynamics
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      – SubjectFull: Physical & theoretical chemistry
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              Text: 2015
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