Innovation in Higher Education: How public universities demonstrate innovative course delivery options
Bibliographic record
Abstract
ABSTRACTThis study examines innovative ways that traditional public universities deliver online and hybrid web-enabled courses. The study finds which actual course features (lectures, readings, discussions, examinations, tutoring, and group work) are more likely found in pure online courses and which in hybrid courses. Results also reveal which of these course features students are likely to prefer to be online for purely online courses and for hybrid courses. Finally, results find which course features are associated with student satisfaction and student achievement. This in-depth study should help traditional public universities to develop more innovative (meaning creating new effective means to improve student satisfaction and achievement) online and partially online programs and courses, as they face competition from newer private online-only universities.Keywords: Online education, web-enabled courses, student achievement, public universitiesIntroductionOnline education is increasing in popularity, and has been the topic of a substantial amount of research (Dykman & Davis, 2008a). Research by the Sloan Consortium indicates that the number of students in the United States taking at least one online course per year reached 3.2 million in 2005 (Allen & Seaman, 2003, 2004, 2005, 2006; Allen, Seaman, & Garrett, 2007; Sloan-C, 2007; see Dykman & Davis, 2008a). More students expect the convenience of online courses and programs. Traditional public universities, facing increasing competition from newer private online-only universities, must innovate their course offerings and programs. In response, many public universities are using technology to develop their own innovative curricula.Therefore, besides online-only universities, many traditional public universities also now offer varying degrees of online education. Online education formats range from a portion of a course to offering entire degree programs (Holstrum & Lloyd-Jones, 1998). A small online segment may be integrated into a traditional course. For example, a professor may elect to use certain course management tools in order to facilitate out-of-class online discussion boards to complement in-class discussions. These tools can also be used to facilitate small group interaction through group chatting and file sharing, that is, to enhance classroom team projects. Moreover, traditional universities may offer entire courses or majors online (Bryant et al., 2005). As such, traditional universities may offer in the online environment entire programs, entire courses, or just specific features inside of a traditional course.Many studies and reports, focusing predominantly on purely online and purely traditional courses, have shown mixed results regarding student satisfaction and achievement (refer to Hara & Kling, 1999; Hirschheim, 2005; Jackson & Helms, 2008; Klesius, Homan, & Thompson, 1997; Ponzurick, France, & Logar, 2000; Storck & Sproull, 1995, as examples). Therefore, it is important to research this entire range of online education formats offered at traditional universities. To do so, it is important to examine the role and effectiveness of offering specific course features or activities (e.g., lectures, readings and assignments, examinations, participation threats, etc.) This in-depth detail is required to truly understand the nature of this innovation to higher education.Therefore, the current study will attempt to address these issues. This study will address the impact on student satisfaction and achievement of online-only courses and hybrid courses (those using web-enabled technologies) for traditional public universities. Specifically, this study looks at the course features that students would prefer to receive online, and what they actually do receive online. By looking more closely at specific course features, those that students prefer (perhaps because they are convenient), and those that students actually receive in various course formats, we should be better able to understand student satisfaction and student achievement. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".