Online Engineering Course

Overview

In a review of literature pertaining to the online engineering courses, this report provides findings from academic journals published in the past 10 years. We included literature that are relevant and relatively up-to-date. The findings are categorized into (1) academic integrity, (2) assessments, (3) instructional strategies, (4) outcomes, and (5) platforms (online labs).

Summary of Research

Academic Integrity

  • Colwell and Jenks (2005) reported that 75% of students admit to some cheating on online courses. The authors suggested using multiple forms of assessment (papers, written assignments, essay tests, objective tests, etc.), using timed tests, proctored tests, randomized testing, and monitoring a student’s work and grades for sudden unexplained improvement.

  • Arnold (2016) examined whether online formative tests are invitations to cheat. The findings suggested that the likelihood of cheating is negatively related to academic progress. Evidence suggested that while cheating in online formative tests may happen, it does not seem to pay off.

Assessment

  • Fhloinn and Carr (2017) stated that there are diverse formative assessments for engineering mathematics, including in-class exercises, homework, mock examination questions, table quizzes, presentations, critical analyses of statistical papers, peer-to-peer teaching, online assessments and electronic voting systems.

  • In another study, Canfield and Zuccaro (2016) stated that digital homework for engineering students is not a hindrance for learning. With a step-by-step instruction on the implementation, this article is a quality starting point for creating a digital homework system.

  • Elias, Elliott, and Elliott (2017) compared the use of commercial (publisher’s) software and in-house software for the first- and second-year engineering students. Findings include that the first-year students found the commercial software less helpful, while second-year students found the in-house program more helpful; but, overall, the class performance was better and the number of students who failed the course was reduced when the online assignments were used.

  • Balascio (2017) reaffirmed the above finding, stating that using online exercises would lead to a significant reduction of cheating and provision of a more individualized instruction and interaction.

Outcomes

  • In a study comparing learning outcomes between remote/virtual labs and traditional labs, Brinson (2015) concluded that virtual/remote labs showed equal or greater outcome achievement. The Knowledge and understanding (K) outcome of the KIPPAS tool is most frequently assessed whereas quizzes/exams are the most frequently used tools for evaluating outcome achievement.

  • Scott, Khoo, Peter, and Round (2016) stated that using videos for lecture delivery is the most helpful activity in a first-year electronic engineering course. Findings suggested that students are more on tasks in the labs and the problem exercises worked well.

  • Lawanto et al., (2014) reported that when students find the course activity important and interesting, student performance would increase. That means the course designer may consider constructing a learning environment that highlights the importance and utility of the course (e.g., provision of rationale for online course activities)

Platform (Online Labs)

  • Okutsu, DeLaurentis, Brophy, and Lambert (2013) reported that the exam scores of the virtual-world group and the real-world group did not find significant difference between the two groups, indicating that the virtual-world is a feasible platform to teach early engineering courses.

  • Potkonjak et al., (2016) provided a well-organized list of online labs for online courses on science, technology and engineering, using four criteria. If designers/faculty consider implementing online labs, this article serves a great starting point.

Suggestion for Implementations

How should this topic be implemented in an online course

References

  • Arnold, I. J. (2016). Cheating at online formative tests: Does it pay off?. The Internet and Higher Education, 29, 98-106.

  • Colwell, J. L., & Jenks, C. F. (2005, October). Student ethics in online courses. In Frontiers in Education, 2005. FIE'05. Proceedings 35th Annual Conference (pp. T2D-T2D). IEEE.

  • Ní Fhloinn, E., & Carr, M. (2017). Formative assessment in mathematics for engineering students. European Journal of Engineering Education, 42(4), 458-470. doi:10.1080/03043797.2017.1289500

  • Canfield, S. L., & Zuccaro, S. G. (2016). Digital homework for kinematics and dynamics of machinery. International Journal of Mechanical Engineering Education, 44(2), 165-182. doi:10.1177/0306419016641008

  • Elias, A. L., Elliott, D. G., & Elliott, J. A. (2017). Student perceptions and instructor experiences in implementing an online homework system in a large second-year engineering course. Education for Chemical Engineers, 21, 40-49.

  • Balascio (2017). Pedagogical Considerations in Use of Online Problem Sets in Technical Courses. Proceedings American Association for Engineering Education. Retrieved from: https://www.asee.org/public/conferences/78/papers/17753/view.

  • Brinson, J. R. (2015). Learning outcome achievement in non-traditional (virtual and remote) versus traditional (hands-on) laboratories: A review of the empirical research. Computers & Education, 87, 218-237.

  • Scott, J., Khoo, E., Peter, M., & Round, H. (2016). Flipped classroom learning in a large introductory undergraduate engineering course. In 27th Annual Conference of the Australasian Association for Engineering Education: AAEE 2016 (p. 690). Southern Cross University.

  • Lawanto, O., Santoso, H. B., Goodridge, W., & Lawanto, K. N. (2014). Task value, self-regulated learning, and performance in a web-intensive undergraduate engineering course: how are they related?. Journal of Online Learning and Teaching, 10(1), 97.

  • Okutsu, M., DeLaurentis, D., Brophy, S., & Lambert, J. (2013). Teaching an aerospace engineering design course via virtual worlds: A comparative assessment of learning outcomes. Computers & Education, 60(1), 288-298.

  • Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrović, V. M., & Jovanović, K. (2016). Virtual laboratories for education in science, technology, and engineering: A review. Computers & Education, 95, 309-327.


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