Show simple item record

dc.contributor.authorEly, Susan
dc.date2022-02-10
dc.date.accessioned2022-02-09T15:51:18Z
dc.date.available2022-02-09T15:51:18Z
dc.identifier.urihttp://hdl.handle.net/20.500.12419/740
dc.description.abstractEngineering students in every discipline complete numerous courses that require complex problem- solving methodologies based on quantitative reasoning. While engineering courses have various areas of focus, the nature of problem-solving is often found to be similar in approach. Many faculty find that errors in student work are due to fundamental flaws in the problem-solving approach, rather than mistakes in computation. Engineering faculty express frustration when grading papers that incorrectly interpret the problem statement or fail to follow the problem-solving approach demonstrated frequently in class. Students are also frustrated by their lack of success and inability to independently solve problems that seemed clear during lecture. In a review of engineering coursework at the University of Southern Indiana, it was found that many of the courses that require extensive quantitative analysis also had a low completion rate: that is, many students who took the course withdrew prior to completion or had to take the course again due to receiving a failing grade. Faculty from a wide variety of engineering programs across the nation have voiced similar frustrations – students come to class with a preconceived notion of the course being difficult but fail to follow the established problem-solving methods provided during instruction. From a faculty perspective, if students followed the methodology presented, the course would not feel so difficult. This difference in perception between faculty and students, as well as the pre-conceived notion of difficulty seems to hinder student success. This research aims to look more closely at the differences in perceived difficulty of the problem-solving process to aid in student persistence and success in quantitative based engineering coursework. Therefore, this research aims to answer the following questions: do students and faculty rate the perceived difficulty and importance of problem-solving steps and does the students problem-solving process (order, perceived difficulty and importance) correlate to overall course success. Research has found that self-efficacy for self-regulated learning has a critical relationship to persistence within a class, a program of study and completion of a degree [1]. That is to say, a student’s ability to take control of their learning and view their learning potential with confidence will positively impact their academic success for both specific courses and academic progress as a whole [1]. Self-efficacy has been shown to directly impact anxiety within STEM coursework, decreasing student success and persistence in courses with a high perceived level of difficulty [2]. This perceived difficulty correlation to poor academic performance supports other work on expectancy-value theory, where academic achievement is limited by students’ perceived ability for success. In fact, some studies have shown perceived difficulty as a predictor of overall course performance [2, 3]. While studies have found students rate their faculty as effective, despite perceived levels of difficulty in the coursework, it is noted that perceived difficulty in coursework can relate to workload, number of exams given or the actual course material, making it difficult to determine what specific course feature or subject was experienced as “difficult” from the student’s perspective [3]. This variability in perceived difficulty can confound faculty who are trying to aid students in learning or make adjustments to their curriculum. However, a student’s fear of academic failure can cause them to procrastinate in assignments, not attend class or otherwise hinder their academic preparation, resulting in the poor performance and poor persistence [4]. This creates a difficulty in the classroom for both teachers and learners: course materials can help to support student learning, but student perceptions about course content can negatively influence their learning outcomes. Therefore, course developers and faculty need to understand student perceptions of the course material to better promote positive learning [5]. To further explore this issue, research was conducted to understand differences in approaches to problem-solving, as well as perceived importance of each step within the process. Furthermore, students were surveyed to understand the relationship between the problem-solving process steps, and the differences in perceived importance and difficulty for each process step. To accomplish this, students completed a survey in which they created a process map of problem-solving steps and rated the perceived difficulty and importance of each step using a Likert-scale. Faculty completed this same survey with their own process maps and Likert ratings. Comparison between student and faculty process steps, as well as Likert response data, were analyzed. Finally, correlations were made between the students’ final course grade and their problem-solving approach. When analyzing the data, it became apparent that students did not uniformly begin with examining the problem. This brings into question both how problem-solving is taught in engineering and whether traditional teaching methodologies place undue emphasis on computation rather than qualitative analysis of a given situation. This presentation will review the results of the research as well as discuss potential classroom implications. References [1] M. Morelli, A. Chirumbolo, R. Baiocco, E. Cattelino, “Academic Failure” Individual, Organizational and Social Factors,” Educational Psychology, vol. 27, no. 2, pp. 167-175, 2021. [2] B. England, J. Brigati, E. Schussler and M. Chen, “Student anxiety and perception of difficulty impact performance and persistence in introductory biology courses,” CBE – Life Sciences Education, vol. 18, no. 21, pp. 1-13, Summer 2019. [3] A. Joyce, “Course difficulty and its association with student perceptions of teaching and learning,” Kentucky Journal of Excellence in College Teaching and Learning, vol. 14, pp.54-62, 2016. [4] T. Bledsoe and J. Baskin, “Recognizing student fear: The elephant in the classroom,” College Teaching, vol. 62, pp. 32-41, 2014. [5] J. Wall and J. Knapp, “Learning computer topics in undergraduate Information Systems courses: Managing perceived difficulty,” Journal of Information Systems Education, vol. 25, no. 3, pp. 245-259, Fall 2014.
dc.subjectproblem solvingen_US
dc.subjectperception differencesen_US
dc.subjectperceived difficultyen_US
dc.titleWhat’s the problem? Perceptions in Problem Solving Methodologiesen_US
refterms.dateFOA2022-02-10T14:04:08Z
html.description.abstract<p>Engineering students in every discipline complete numerous courses that require complex problem- solving methodologies based on quantitative reasoning. While engineering courses have various areas of focus, the nature of problem-solving is often found to be similar in approach. Many faculty find that errors in student work are due to fundamental flaws in the problem-solving approach, rather than mistakes in computation. Engineering faculty express frustration when grading papers that incorrectly interpret the problem statement or fail to follow the problem-solving approach demonstrated frequently in class. Students are also frustrated by their lack of success and inability to independently solve problems that seemed clear during lecture. In a review of engineering coursework at the University of Southern Indiana, it was found that many of the courses that require extensive quantitative analysis also had a low completion rate: that is, many students who took the course withdrew prior to completion or had to take the course again due to receiving a failing grade. Faculty from a wide variety of engineering programs across the nation have voiced similar frustrations &ndash; students come to class with a preconceived notion of the course being difficult but fail to follow the established problem-solving methods provided during instruction. From a faculty perspective, if students followed the methodology presented, the course would not feel so difficult. This difference in perception between faculty and students, as well as the pre-conceived notion of difficulty seems to hinder student success. This research aims to look more closely at the differences in perceived difficulty of the problem-solving process to aid in student persistence and success in quantitative based engineering coursework. Therefore, this research aims to answer the following questions: do students and faculty rate the perceived difficulty and importance of problem-solving steps and does the students problem-solving process (order, perceived difficulty and importance) correlate to overall course success.</p> <p>Research has found that self-efficacy for self-regulated learning has a critical relationship to persistence within a class, a program of study and completion of a degree [1]. That is to say, a student&rsquo;s ability to take control of their learning and view their learning potential with confidence will positively impact their academic success for both specific courses and academic progress as a whole [1]. Self-efficacy has been shown to directly impact anxiety within STEM coursework, decreasing student success and persistence in courses with a high perceived level of difficulty [2]. This perceived difficulty correlation to poor academic performance supports other work on expectancy-value theory, where academic achievement is limited by students&rsquo; perceived ability for success. In fact, some studies have shown perceived difficulty as a predictor of overall course performance [2, 3]. While studies have found students rate their faculty as effective, despite perceived levels of difficulty in the coursework, it is noted that perceived difficulty in coursework can relate to workload, number of exams given or the actual course material, making it difficult to determine what specific course feature or subject was experienced as &ldquo;difficult&rdquo; from the student&rsquo;s perspective [3]. This variability in perceived difficulty can confound faculty who are trying to aid students in learning or make adjustments to their curriculum. However, a student&rsquo;s fear of academic failure can cause them to procrastinate in assignments, not attend class or otherwise hinder their academic preparation, resulting in the poor performance and poor persistence [4]. This creates a difficulty in the classroom for both teachers and learners: course materials can help to support student learning, but student perceptions about course content can negatively influence their learning outcomes. Therefore, course developers and faculty need to understand student perceptions of the course material to better promote positive learning [5].</p> <p>To further explore this issue, research was conducted to understand differences in approaches to problem-solving, as well as perceived importance of each step within the process. Furthermore, students were surveyed to understand the relationship between the problem-solving process steps, and the differences in perceived importance and difficulty for each process step. To accomplish this, students completed a survey in which they created a process map of problem-solving steps and rated the perceived difficulty and importance of each step using a Likert-scale. Faculty completed this same survey with their own process maps and Likert ratings. Comparison between student and faculty process steps, as well as Likert response data, were analyzed. Finally, correlations were made between the students&rsquo; final course grade and their problem-solving approach.</p> <p>When analyzing the data, it became apparent that students did not uniformly begin with examining the problem. This brings into question both how problem-solving is taught in engineering and whether traditional teaching methodologies place undue emphasis on computation rather than qualitative analysis of a given situation. This presentation will review the results of the research as well as discuss potential classroom implications.</p> <p>References</p> <p>[1] M. Morelli, A. Chirumbolo, R. Baiocco, E. Cattelino, &ldquo;Academic Failure&rdquo; Individual, Organizational and Social Factors,&rdquo; Educational Psychology, vol. 27, no. 2, pp. 167-175, 2021.</p> <p>[2] B. England, J. Brigati, E. Schussler and M. Chen, &ldquo;Student anxiety and perception of difficulty impact performance and persistence in introductory biology courses,&rdquo; CBE &ndash; Life Sciences Education, vol. 18, no. 21, pp. 1-13, Summer 2019.</p> <p>[3] A. Joyce, &ldquo;Course difficulty and its association with student perceptions of teaching and learning,&rdquo; Kentucky Journal of Excellence in College Teaching and Learning, vol. 14, pp.54-62, 2016.</p> <p>[4] T. Bledsoe and J. Baskin, &ldquo;Recognizing student fear: The elephant in the classroom,&rdquo; College Teaching, vol. 62, pp. 32-41, 2014.</p> <p>[5] J. Wall and J. Knapp, &ldquo;Learning computer topics in undergraduate Information Systems courses: Managing perceived difficulty,&rdquo; Journal of Information Systems Education, vol. 25, no. 3, pp. 245-259, Fall 2014.</p>en_US
dc.contributor.affiliationUniversity of Southern Indianaen_US


Files in this item

Thumbnail
Name:
SEly-TLS2022-Final.pdf
Size:
1.208Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record