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With the increasing prevalence of computer-based examinations in universities, the Fundamentals of Engineering for Honors (FEH) program at The Ohio State University conducted a study examining the effect of test mode on student exam performance. Computer-based exams have many advantages for the instructor over paper-based exams including automated grading, ease of distribution, reduced paper usage, and the ability to see student exam statistics instantly. This study was conducted during the fall semester and consisted of two midterm exams and a final exam. The exam questions being considered in this study included multiple choice, true/false, multiple select, and fill in the blank questions. For each exam, there were two parts (1 and 2), that each student took with separate modes, either on computer or on paper. The part (1 or 2) each student took in each mode was flipped for half the students. After analyzing the results, the exam score differences between computer and paper were not statistically significant in 5 out of 6 exam parts analyzed. While the exam scores displayed limited differences, the students reported an overwhelming preference for the paper exams (86%) over the computer exams (5%). These results indicate that even though computer exams have similar performance to their paper counterparts, the students prefer the paper exams. Therefore, because performance is similar, future studies should explore improving the student experience in the computer exam environment while still realizing the advantages of computer-based examinations. [ABSTRACT FROM AUTHOR]

Web-native textbooks use practice questions and animations to improve student performance to help learn and visualize concepts. Creating practice questions and animations is time intensive. This paper investigates whether having students create and/or rate practice questions and animations--student crowdsourcing--can lead to good quality items. For animations, we conducted experiments involving 587 participants from a basic computing technology course. Students were asked to create animations of a topic, and a professor and fellow students rated those animations. Some students showed the ability to create quality animations: 2 of 19 completed animations were rated a "5" on a 1 to 5 scale (5 is best) by a professor / professional animation author. Furthermore, some students showed the ability to effectively rate student-created animations; the top 10% of student ratings was strongly correlated with the professor ratings with R-value = 0.88 (p-value < 0.001). For questions, we conducted experiments involving 25 participants from an introductory embedded programming course. Students were asked to create and rate practice questions for various embedded programming topics. Some students could effectively rate questions: the average of the top 20% of student ratings was strongly correlated with the professor rating with R-value = 0.82 (p-value = 0.02). However, students did not show the ability to create good question; no student's question was professor-rated above a 4. The common problem seen was an inability to write correct and precise English. [ABSTRACT FROM AUTHOR]

For large enrollment courses, such as Statics, Dynamics, Fluid Mechanics, Solid Mechanics, Thermodynamics, the use of computers (laptops and tablets) in the classroom can save instructor time. However, there are numerous problems with computer-based exams, especially when the students are allowed to access online course materials (eBook, homework, etc). Previously, the author used student-supplied laptops for web-based exams in the classroom, but this has become problematic over the years due to the increased sophistication of communication software (Twitter, Facebook, Skype, SnapChat, etc.). It is no longer reasonable to expect the instructor and TAs to be able to monitor student laptops during exams. To solve this issue, android-based tablets with special apps have been developed and implemented into two fundamental engineering courses, Fluid Mechanics and Solid Mechanics (Mechanics of Materials). The paper first examines both the selection process for the Android-based tablets and the development process for applications (apps) required for testing. Both Android and iOS tablets were considered. Based on cost and ease of system customization, Android-based tablets were selected. Two different apps were developed for use for tests. The first app, "examApp" permits the student to access the online text and it records the student's choices. It has numerous security features that limit access to the exam only on the tablets provided and only during the test time. All graphics are vector-based so they are crisp on high resolution screens. Included in the examApp was an admin (or instructor) page that provides the instructor and TAs real-time information about the exam while in progress. This includes scores, percent correct for a given problem, students activity, graphs, and direct communications to all students. The second app, "eBookApp", allows the student access to the online eBook used for the class. However, it blocks the student from other online web site or material. The Android operating system itself was modified to limit access to standard apps like email, app stores, social networks, and even browsers. The apps were developed using Abobe AIR development framework due to its relatively easy development of web and mobile apps when compared to native programming or HTML5 with JavaScript. AIR also avoids programming the same app three times (web browsers, Android and iOS). The successful results (and lessons learned) using tablets for in-class testing for multiple engineering courses are presented. [ABSTRACT FROM AUTHOR]

Understanding technical vocabulary is often a desired learning outcome in engineering education, and a significant part of professional communication in the engineering profession. Language used in engineering education plays a key role in creating an accessible and inclusive learning environment. The corpus of language common to both the instructor and student ought to converge as the student masters the course content. Instructors may currently use techniques to help identify this vocabulary, including referring to glossaries and increasing the frequency of their use in the classroom. There is an opportunity to increase transparency and accessibility to such vocabulary by developing an automated software-based tool that can be used by instructors to create customized course-specific wordlists for their courses. Using text extracted from instructional material in a course, the algorithm developed for this study is able to hierarchically identify and display course-specific terminology using principles from artificial intelligence, linguistics, higher education, and industrial engineering. Grounded in the theory of Universal Instructional Design, these wordlists can be integrated into a syllabus and then be used as a teaching aid to promote an accessible engineering education. The goal is to reduce barriers to learning by developing an explicitly-identified and robust list of vocabulary for all students in a given course. Creating an automated program that improves vocabulary information over time keeps it relevant and usable by instructors as well as students. Presently, there is no automated method to develop course-specific vocabulary lists. To fill this gap, the authors have created a computer program, using a repository of over 2200 engineering exams since the year 2000 from the University of Toronto, which automatically identifies domain-specific terms on any given engineering exam. Specifically, each word from each exam is digitized and computed against others using a modified form of the Term-Frequency Inverse Document-Frequency (TF-IDF) algorithm to generate lists of context-specific characteristic terms. This well-known algorithm is used in the field of computational linguistics as a method of identifying words characteristic to a document, given a comparator set of documents. In this work, a modified approach has been developed that uses several comparator sets to produce a list of engineering vocabulary for a course. The effectiveness of this approach is evaluated by comparing the results to the judgment of subject-matter experts. This paper will use the data gathered to discuss the efficacy of this automated program in the context of engineering research methods, and will identify ways in which to make this program accessible to, and usable by, more educators in the field of engineering education. [ABSTRACT FROM AUTHOR]

"Experientially Correct Introduction to Engineering" (ECIE) is a loosely defined term coined by the authors to refer to any introductory academic engineering exercise that deliberately aims to incorporate as many aspects of real-engineering as possible in order to create an experience that accurately reflects the practice of engineering. For incoming students, up to the point when they arrive on a college campus, most introductory engineering activity is intended to entice or awaken the student to the possibilities of engineering. ECIE exercises, on the other hand, aim for accuracy of practice as a counter measure to downstream attrition resulting from shifting perceptions of engineering as students progress through the curriculum. In this paper, we discuss the challenges and the effects of designing two six-week summer bridge ECIE modules for prospective female engineering students who have no prior technical training and no prior skill in the supporting trades. Details of module development philosophy including choice of activity, technical difficulty, relevance, disciplinary diversity are discussed. Effects of the modules are assessed by student survey. It is found that what students reported to be their greatest surprise about engineering based on their ECIE module experience can be generally grouped into 4 recurring themes: 1) Engineering can be largely trial-and-error and not necessarily math-intensive. 2) Engineering is highly demanding in terms of attention to detail. 3) Engineering can have a very large impact on society 4) Engineering can be an isolating discipline for the practitioner. Suggestions on how this insight might be used to attract and retain more female students to engineering are provided. [ABSTRACT FROM AUTHOR]

The present paper focuses on the errors that students made on a first year engineering dynamics final exam. An error classification scheme, based on Action Theory, is used to classify errors as either mistakes or slips in logic. Simple rules are then developed for a computer to be capable of categorizing errors based on a priori indicators such as: the student's experience level and the topic's priority on the courses concept inventory as well as a posteriori indicators such as the frequency of the error within the exam. The assessment algorithm is then trained and optimized. The resulting algorithm is tested by comparing the results with a second, independent, expert. Results of the study are then discussed. [ABSTRACT FROM AUTHOR]