Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students’ solutions to a complex, openended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in a course centered around modeling?.
Students’ solutions to an openended problem across multiple sections of an introductory programming course were explored. These sections were all divided across two groups: (1) experimental group  these sections discussed and utilized mathematical and computational models explicitly throughout the course, and (2) comparison group  these sections focused on developing algorithms and writing code with a more traditional approach. All sections required students to complete a common openended problem that consisted of two versions of the problem (the first version with smaller data set and the other a larger data set). Each version had two submissions – (1) a mathematical model or algorithm (i.e. students’ written solution potentially with tables and figures) and (2) a computational model or program (i.e. students’ MATLAB code). The students’ solutions were graded by student graders after completing two required training sessions that consisted of assessing multiple sample student solutions using the rubrics to ensure consistency across grading. The resulting assessments of students’ works based on the rubrics were analyzed to identify patterns students’ submissions and comparisons across sections.
The results identified differences existing in the mathematical and computational model development between students from the experimental and comparison groups. The students in the experimental group were able to better address the complexity of the problem. Most groups demonstrated similar levels and types of change across the submissions for the other dimensions related to the purpose of model components, addressing the users’ anticipated needs, and communicating their solutions. These findings help inform other researchers and instructors how to help students develop mathematical and computational modeling skills, especially in a programming course. This work is part of a larger NSF study about the impact of varying levels of modeling interventions related to different types of models on students’ awareness of different types of models and their applications, as well as their ability to apply and develop different types of models.
more »
« less
Comparing students’ solutions to an openended problem in an introductory programming course with and without explicit modeling interventions
Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students’ solutions to a complex, openended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in a course centered around modeling?. Students’ solutions to an openended problem across multiple sections of an introductory programming course were explored. These sections were all divided across two groups: (1) experimental group  these sections discussed and utilized mathematical and computational models explicitly throughout the course, and (2) comparison group  these sections focused on developing algorithms and writing code with a more traditional approach. All sections required students to complete a common openended problem that consisted of two versions of the problem (the first version with smaller data set and the other a larger data set). Each version had two submissions – (1) a mathematical model or algorithm (i.e. students’ written solution potentially with tables and figures) and (2) a computational model or program (i.e. students’ MATLAB code). The students’ solutions were graded by student graders after completing two required training sessions that consisted of assessing multiple sample student solutions using the rubrics to ensure consistency across grading. The resulting assessments of students’ works based on the rubrics were analyzed to identify patterns students’ submissions and comparisons across sections. The results identified differences existing in the mathematical and computational model development between students from the experimental and comparison groups. The students in the experimental group were able to better address the complexity of the problem. Most groups demonstrated similar levels and types of change across the submissions for the other dimensions related to the purpose of model components, addressing the users’ anticipated needs, and communicating their solutions. These findings help inform other researchers and instructors how to help students develop mathematical and computational modeling skills, especially in a programming course. This work is part of a larger NSF study about the impact of varying levels of modeling interventions related to different types of models on students’ awareness of different types of models and their applications, as well as their ability to apply and develop different types of models.
more »
« less
 Award ID(s):
 1827392
 NSFPAR ID:
 10182819
 Date Published:
 Journal Name:
 ASEE Annual Conference proceedings
 ISSN:
 15244644
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
More Like this


This complete research paper describes the impact of a modeling intervention on firstyear engineering students’ modeling skills in an introductory computer programming course. Five sections of the firstyear engineering introductory programming course at a private, STEM+Business institution were revised to center around modeling concepts. These five sections made up the experimental group for this study. The comparison group consisted of four sections of the course that were not revised. Students in all these sections were given two different versions of a modeling problem two times in the semester to test their progress in gaining modeling skills. Each version required two submissions – a written solution and a coded solution. The assessment of these four submissions based on the three established dimensions of modeling were quantitatively analyzed in this study. The three dimensions within mathematical modeling that were the focus of this study were mathematical model complexity, modifiability, and reusability. Mathematical model complexity is being able to address the complexity of the problem. Modifiability addresses the generalizability of the model solution. Reusability is showing an understanding of the problem and the user. Statistical analysis showed that students in the experimental group had more gains in their demonstrated modeling abilities across all three dimensions than the students in the comparison group. This study demonstrated that intentional and explicit instructional strategies targeting model development resulted in greater gains in students’ demonstrated modeling skills and both their written and coded solutions to a complex modeling problem.more » « less

Security is a critical aspect in the design, development, and testing of software systems. Due to the increasing need for securityrelated skills within software systems and engineering, there is a growing demand for these skills to be taught at the university level. A series of 41 security modules was developed to assess the impact of these modules on teaching critical cyber security topics to students. This paper presents the implementation and outcomes of the first set of six security modules in a Freshman level course. This set consists of five modules presented in lectures as well as a sixth module emphasizing encryption and decryption used as the semester project for the course. Each module is a collection of concepts related to cyber security. The individual cyber security concepts are presented with a general description of a security issue to avoid, sample code with the security issue written in the Java programming language, and a second version of the code with an effective solution. The set of these modules was implemented in Computer Science I during the Fall 2019 semester. Incorporating each of the concepts in these modules into lectures depends on both the topic covered and the approach to resolving the related security issue. Students were introduced to computing concepts related to both the security issue and the appropriate solution to fully grasp the overall concept. After presenting the materials to students, continual review with students is also essential. This reviewal process requires exploring usecases for the programming mechanisms presented as solutions to the security issues discussed. In addition to the security modules presented in lectures, students were given a handson approach to understanding the concepts through ModelEliciting Activities (MEAs). MEAs are openended, problemsolving activities in which groups of three to four students work to solve realistic complex problems in a classroom setting. The semester project related to encryption and decryption was implemented into the course as an MEA. To assess the effectiveness of incorporating security modules with the MEA project into the curriculum of Computer Science I, two sections of the course were used as a control group and a treatment group. The treatment group included the security modules in lectures and the MEA project while the control group did not. To measure the overall effectiveness of incorporating security modules with the MEA project, both the instructor’s effectiveness as well as the student’s attitudes and interest were measured. For instructors, the primary question to address was to what extent do instructors change their attitudes towards student learning and their teaching practices because of the implementation of cyber security modules through MEAs. For students, the primary question to address was how the inclusion of security modules with the MEA project improved their understanding of the course materials and their interests in computer science. After implementing security modules with the MEA project, students showed a better understanding of cyber security concepts and a greater interest in broader computer science concepts. The instructor’s beliefs about teaching, learning, and assessment shifted from teachercentered to studentcentered, during his experience with the security modules and MEA.more » « less

Background To succeed in engineering careers, students must be able to create and apply models to certain problems. The different types of models include physical, mathematical, computational, graphical, and financial, which are used both in academics, research, and industry. However, many students struggle to define, create, and apply relevant models in their engineering courses. Purpose (Research Questions) The research questions investigated in this study are: (1) What types of models do engineering students identify before and after completing a firstyear engineering course? (2) How do students’ responses compare across different courses (a graphical communications course  EGR 120 and a programming course  EGR 115), and sections? Design/Methods The data used for this study were collected in two introductory firstyear engineering courses offered during Fall 2019, EGR 115 and EGR 120. Students’ responses to a survey about modeling were qualitatively analyzed. The survey was given at the beginning and the end of the courses. The data analyzed consisted of 560 pre and post surveys for EGR 115 and 384 pre and post surveys for EGR 120. Results Once the analysis is complete, we are hoping to find that the students can better define and apply models in their engineering courses after they have completed the EGR 115 and/or EGR 120 courses.more » « less

Problem solving is a signature skill of engineers. Incorporating videos in engineering education has potential to stimulate multisenses and further open new ways of learning and thinking. Here, problem solving was examined on problems written by previous students that applied course concepts by reverse engineering the actions in videos. Since the videos usually come from YouTube, the studentwritten problems are designated YouTube problems. This research focused on examining the rigor of YouTube problems as well as students’ problemsolving skills when solving YouTube problems compared to Textbook problems. A quasiexperimental, treatment/control group design was employed, and data collected was evaluated using multiple instruments. NASA Task Load Index survey was used to collect 1200 ratings that assessed rigor of homework problems. Problemsolving ability was assessed using a previouslydeveloped rubric with over 2600 student solutions scored. In the treatment group where students were assigned ten Textbook and nine YouTube problems, students reported an overall similarity in rigor for both YouTube and Textbook problems. Students in the treatment group displayed 6% better problem solving when completing YouTube problems compared to Textbook problems. Although higher perceptions of problem difficulty correlated with lower problemsolving ability across both groups and problem types, students in the treatment group exhibited smaller decreases in problemsolving ability as a result of increasing difficulty in the Textbook problems. Overall, studentwritten problems inspired by YouTube videos can easily be adapted as homework practice and possess potential benefits in enhancing students’ learning experience. Link: https://www.ijee.ie/contents/c370521.htmlmore » « less