Hello everyone. My name is Kaku, an academic cooperative researcher.
As I told you before, my research is “Development of Content and Language Integrated Learning (CLIL) in Japanese Language Education based on Instructional Design (ID)”. In my research, I design a checklist on CLIL lesson design based on ID theory. Recently, I have been reading papers on checklists for lesson design because I needed to revise the checklist for my research and also to design a questionnaire to evaluate the checklist.
In this English literature seminar, I will present a paper on the development of checklists for online class design and user recognition.
Paper Title: An online course design checklist: development and users’ perceptions
Journal: Journal of Computing in Higher Education 31, 156-172.
Authors: Sally J. Baldwin · Yu‑Hui Ching
Year of publication: 2019
This study investigated users’ perceptions of an online course design checklist. We created the Online Course Design Checklist (OCDC) to help highlight basic criteria that may improve the quality of online classes. We then surveyed class designers’ perceptions of the OCDC.
It has been noted that course design is a fundamental principle upon which classes are conducted (Koehler and Mishra 2005, p. 135). Online classes may also be designed by instructional designers, instructors, or a combination of these professionals. In designing effective online classes, it is important to maximize the satisfaction of and promote learning outcomes in a different format than traditional instruction (e.g., face-to-face, online, blended, etc.). However, this paper finds that current instructors of online classes lack theory and experience in class design. And in their evaluation, there are currently available evaluation tools for online classes. However, they are too large and difficult to use. For example, the Open SUNY Course Quality Review Rubric (OSCQR), with its 50 indicators, is too broad. Therefore, this paper suggests that already existing design tools need to be further simplified.
The paper proposes a checklist that highlights criteria that may improve the quality of online class design.
The study attempts to build a checklist based on previous studies (Chao et al. 2010; Choi and Ahn 2010; Yang and Cornelious 2005) that have identified the importance of quality guidelines in online education. This study has developed a one-page checklist that collects only the design elements that must be present when designing an online class.
Phase of Development
The first step is to identify the items that need to be included in the checklist. The criteria for selecting these items are considered the most important and “can’t miss” items when designing a class. We then review the literature on current assessment methods, multimedia and instructional design to develop the checklist. The ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) was used to develop the OCDC.
Phase of user perception survey
Participants and Background
PARTICIPANTS: Twelve were teachers, one was an instructional designer, one was a student, and the remaining five were in other professions among graduate students enrolled in an online master’s degree program at a state university in the Northwest United States. Participants’ experience designing online classes ranged from none at all (n=4) to having designed 5 or more classes (n=7).
METHODS: Participants designed online classes using OCDC. Then, at the end of the class, an online questionnaire was administered for participants to fill in their opinions about OCDC. The questionnaire was designed to ask participants how they used OCDC, their satisfaction with OCDC, whether their use of OCDC influenced their course design, and to solicit their opinions.
RESULTS
User Experience and Satisfaction
Twenty-one percent of participants (n = 4) indicated that they changed their lesson design process significantly, 26% of participants (n = 5) moderately, 47% of participants (n = 9) slightly, and one did not change it at all.
Seventy-nine percent of participants (n = 15) indicated that they used OCDC at the end of the design process. Overall, 63% of participants were satisfied or very satisfied with the use of OCDC (n = 12). The remaining 37% of participants indicated that they neither liked nor disliked OCDC (n = 7); 79% of participants reported being very satisfied (n = 4) or satisfied (n = 11) with the completed lesson design.
Checklist Design
All participants (N=19) reported that they found the OCDC easy to understand.
Future Use
64% of participants reported that they are likely (n = 6) or very likely (n = 6) to use OCDC when designing future lessons.
Suggested Changes
31% (n = 6) of participants wanted the checkboxes to be marked with interactive checkmarks to note progress. Some participants also suggested adding additional explanations.
CONCLUSION
The authors in this study designed, developed, and tested an online course design checklist with the goal of helping online instructors design quality online courses. Results indicate that the OCDC is a promising tool to assist in the design and development of online course content.
The OCDC means that the criteria are applicable to all experience levels of online instructors designing online courses. Although there was a suggestion to add additional explanations, we will maintain the current layout in order to keep the OCDC simple and user-friendly. However, it was also suggested that users could be provided with links to examples of the various criteria listed in the OCDC. Future research should include interviewing participants to gather more details about how the checklist affects lesson design, as well as experimenting with adding and removing criteria.
My own impression of the paper is that the items on the checklist and the questions to evaluate the checklists were helpful to my own research and I would definitely use them. However, as the author himself states in the paper, the small number of participants is a limitation of this study. Also, if it is known that the number of participants is small, I think it would be better to consider taking thicker qualitative data, such as those who include interviews after the questionnaire, etc. In my own research, I would like to take qualitative data to add depth to the evaluation.
