Revising the ABET Information Technology Criteria to Reflect the IT 2017 Curriculum Guidelines

Developing curriculum guidelines for high quality, rigorous degree programs in Information Technology (IT) requires broad engagement of international perspectives and critical input from the industry sector and computing professional societies. As the computing field rapidly evolves, ACM and IEEE Computer Society have partnered to regularly update curriculum reports, including curriculum guidelines for baccalaureate IT programs, also known as the IT2017 report. Released in December 2017, the report provides the framework for revising the ABET IT program criteria used to accredit undergraduate IT programs. The panelists will describe different perspectives and rationales for the proposed revisions, will address potential obstacles in formulating theses revisions, and will solicit feedback for both the impact and possible improvements for these revisions

Effects of Real-World Experiences in Active Learning (R.E.A.L.) Applied in an Information Systems Data Communication and Networking Course

The purpose of this study was to determine if the use of Real-World Experiences in Active Learning (R.E.A.L.) impacted student learning outcomes in an undergraduate information systems (IS) data communication and networking course. A quasi-experimental, quantitative approach was used to investigate whether the R.E.A.L. treatments, used as active learning strategies, significantly impacted student performance, short-term retention, long-term retention, and student engagement. The data collection was completed in one semester. Participants were students enrolled in an IS data communication and networking course during the Fall 2019 semester. The students, enrolled in the two sections of the course, were taught using a crossover design where each student received eight treatments. The researcher of the study served as the instructor for both sections. The research question and four hypotheses were analyzed using repeated measures MANCOVA and multi-level modeling (MLM). After a statistical analysis of the direct effects of the R.E.A.L. treatments on student performance, short term retention, long term retention, and engagement, none of the four hypotheses were fully supported. The results indicated that the R.E.A.L. xiii treatments did not significantly impact the student learning outcomes from the course. Research findings partially supported hypothesis H1 indicating that age, ethnicity, and major have some influence on students’ performance and age may have some influence on short-term retention. Statistically significant results were obtained for the H1a Network treatment (F(1,28) = 6.033, p = 0.021, partial η2 = 0.177), meaning that the mean for the H1a Network treatment (M = 90.842) was significantly different than the lecture mean (M = 75.533). The H1b Handshake treatment (F(1,28) = 15.405, p = .001, partial η2 = 0.355) and the H1c Wireless treatment (F(1,28) = 11.385, p = .002, partial η2 = 0.289) produced results in the reverse direction of what was hypothesized, meaning that the mean for the H1b Handshake treatment (M = 49.800) and the H1c Wireless treatment (M = 86.842) were significantly lower than the lecture means for both hypothesis tests. Research findings partially supported hypothesis H2 indicating that age may have influence on short-term retention. Statistically significant results were obtained for the H2e Network speed treatment (F(1,28) = 5.709, p = 0.024, partial η2 = 0.164) and H2f Network management treatment (F(1,28) = 5.654, p = 0.024, partial η2 = 0.163). However, findings from the MLM post hoc tests of direct, interaction, and indirect effects did show some areas for future work in certain demographics, especially gender and ethnicity. Findings of the study were not shown to be significant however, the post hoc testing revealed areas where future work could be beneficial