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Correlating Students' Evaluations Of Their Learning With Class Performance
Author(s) -
Craig Somerton
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--11297
Subject(s) - class (philosophy) , session (web analytics) , mathematics education , computer science , quartile , set (abstract data type) , artificial intelligence , psychology , mathematics , statistics , world wide web , confidence interval , programming language
Results of a study comparing student surveys of their achievement of a course’s learning objectives with the class performance on these learning objectives through graded assignments are presented. The correlation between the two is not as strong as might be expected, though when presented in quartile fashion the student’s perception of their learning as represented by the survey results compares favorably with their achievement on graded assignments. Introduction As part of the its response to Engineering Criteria 2000, each undergraduate course in the Department of Mechanical Engineering at Michigan State University has a published set of course learning objectives (CLO). At the end of each semester, students complete a course learning objective questionnaire in addition to the university’s Student Instructional Rating System (SIRS) form, which is the primary tool used to assess teaching at the university. The course learning objective questionnaire asks the students to evaluate their achievement of the course learning objectives. However, this may not be a true indication of their achievement. In an attempt to assess how true an indicator the CLO survey results are with respect to student learning, a study was undertaken to compare the students' assessment of their learning with their class performance. This study is the focus of this paper. This paper continues by presenting the course learning objectives for the course used in this study. Next the measurement of students’ achievement of the course learning objectives using graded assignments is explained. A comparison of the survey results with the class performance is then presented and discussed. Final remarks conclude the paper. Course Learning Objectives For this study a senior level course in heat transfer (ME 410) was chosen. It is a three credit semester course, meeting three days a week for fifty minutes each class session. The course is required for all mechanical engineering majors, and its topical coverage is typical of the required heat transfer course in most mechanical engineering programs. The class was taught in one large section of fifty-five (55) students. The complete set of course learning objectives for the course is shown in Figure 1. These were developed by the faculty that routinely teach the course approximately one year prior to the department's last ABET visit. It will be clear to heat transfer instructors that some of these objectives are not appropriate or are not worded appropriately. This is due to the faculty’s inexperience in writing course learning objectives. At the end of each semester, students are asked to evaluate their achievement of the course learning objectives. Simultaneously, this form is also used by the college to gather the student assessment of teaching. This form allows for eighteen supplemental questions that are utilized for the course P ge 731.1 “Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition Copyright ” 2002, American Society for Engineering Education” Figure 1 Course Learning Objective for ME 410 1. Students understand and are able to use the conduction, convection and radiation rate equations 2. Students are able to use the conservation of energy to solve problems 3. Students are able to solve one-dimensional heat conduction problems using the energy equation and Fourier’s law 3.1 Students are well versed in the use of the thermal resistance network 3.2 Students can solve one-dimensional problems in radial systems, 3.3 Students can solve problem involving some form of energy generation 3.4 Students are able to solve problems involving extended surfaces 4. Students have an understanding of the analytical and numerical techniques used for solving two dimensional, steady-state and transient heat conduction 5. Students are able to solve simple transient heat conduction problems 5.1 Students are able to use the lumped capacitance method 5.2 Students are able to solve problems where spatial effects are important using approximate methods and the Heisler charts 5.3 Students are able to solve problems with a semi-infinite dimension 5.4 Students are able to solve simple transient problems with multidimensional effects 6. Students are able to solve problems where convection heat transfer is important 6.1 Students understand the origin and implications of boundary layers for laminar & turbulent flows, and their impact on convection heat transfer 6.2 Students are aware of the similarity solutions 6.3 Students understand the origin of relevant dimensionless parameters 6.4 Students understand the implications of Reynolds’ analogy 6.5 Students understand the hydrodynamic and thermal considerations for internal flows 6.6 Students understand the derivation of the energy balance for constant temperature & constant heat flux boundary conditions for internal convection problems 6.7 Students are able to use convection correlations to solve forced convection problems for external and internal flows 6.8 Students understand the important physical aspects of free convection 6.9 Students have knowledge of the governing equation relevant to natural convection 6.10 Students understand the relevant dimensionless numbers for natural convection 6.11 Students are able to use Nusselt number empirical correlations to solve natural convection problems 7. Students are able to solve simple radiation problems 7.1 Students understand concepts such as blackbody , surface emission, absorption, radiosity 8. Students are able to find appropriate view factors, and compute simple radiation exchanges for gray surfaces

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