Session Information
16 SES 14 A, Online and Blended Learning
Paper Session
Contribution
1. Background of the study
1.1. Problem statements regarding digital technologies for education in digital era
With the rapid innovation of digital technology, the digital transformation of education has accelerated, emphasizing the role of digital technologies in teaching and learning more than ever. The use of digital technology (e.g., Kahoot) to enhance interaction in classrooms, employing personalized learning platforms (e.g., ALEKS), and using augmented/virtual reality to enhance the learning presence are no longer exceptional cases but are commonly found in many classes. Thus, digital technology plays a crucial role in improving the efficiency and effectiveness of the teaching and learning environment.
However, Daniela (2019) pointed out that the centrifugal effect of technology can fragment various components of education, such as learning materials, environments, and peer interactions. Empirical studies have also reported that digital usage in education can lead to social and affective challenges (Lemay, Bazelais, & Doleck, 2021). These issues arising from digital technology necessitate strengthening pedagogical perspectives and approaches in instructional design (Daniela, 2019).
In education, digital technologies are emphasized not only as an environment but also as a competence for learners. The Digital Education Action Plan 2021-2027 of the European Commission (2020) highlighted “Enhancing digital skills and competences for the digital transformation” as its second priority. Learner’s digital literacy (Eshet-Alkalai, 2004) significantly impacts learning achievements in technology-based education (Tang & Chaw, 2016). Therefore, in the context of digital education, it is essential to consider digital literacy as a factor influencing learning, and to ensure that the use of technologies in educational processes naturally enhances learners' digital literacy.
1.2. Research idea to address the problem
In this research, we aim to address educational problems arising in the era of digital innovation by enhancing traditional instructional design model, ASSURE, based on technology-related theory.
The ASSURE model (Heinich, Molenda, Russell, & Smaldino, 1999) is an instructional design model to guide the effective integration of media and learning materials into classrooms. It is a generalized instructional design model like the ADDIE and Dick & Carey models, applicable to various situations and contexts. The model, known for its practicality and effectiveness in enhancing learning achievements, has been widely used so far (Kim & Downey, 2016; Lei, 2023).
However, unlike the past when delivery media were predominantly used, recent technologies are characterized by increased complexity and messiness (Ross & Collier, 2016). In this context, inconsiderate adoption of technology without adequately considering learners' readiness or pedagogy can induce techno-stress and may even lead to extraneous cognitive load (Agbu, 2015; Skulmowski & Xu, 2022). Therefore, if the ASSURE model, a widely used instructional design model, is revised to assist in the integration of innovative technologies into education, it is expected to be more beneficial in the digital era.
As a theoretical framework to improve ASSURE, Task-Technology Fit (TTF; Goodhue & Thompson, 1995) can be considered. TTF is defined as “the degree to which a technology assists an individual in performing his or her portfolio of tasks” (p. 216). Applying TTF to learning implies that if there is an appropriate fit between the learner’s digital literacy (individual characteristics), learning activities (task characteristics), and digital technology for education (technology characteristics), the effectiveness of learning is expected to increase.
1.3. Study objectives and research Questions
Building on the limitations of existing instructional design model in the age of innovative technologies, this study aims to revise ASSURE model based on the TTF model. Research questions are as follow:
Q1. Revised ASSURE mode based on the task-technology fit theory (ASSURE-TTF model) is valid?
Q2. Instructional design according to revised ASSURE model con contribute to the integration of innovative technologies into classes?
Method
2. Research design This study conducted a Model Research (Type II), the design and development research methodology of Richey and Klein (2014). Model research allows variations considering the focus of the study: whether it's the development, validation, or evaluation. As this study aims to improve an existing instructional design model, ASSURE model was revised based on the literature review on the ASSURE model and task-technology fit theory in the initial phase of the research process. The revised model was then reviewed for validity by three instructional design experts (Ph.D.). Then, ASSURE-TTF model was modified based on their feedback. To check the usability and feasibility of the model, a cognitive walkthrough with five elementary school teachers will be conducted at the last phase of the study.
Expected Outcomes
3.1. Findings from the first two phases of the research procedure Based on the literature review, the ASSURE-TTF model was revised as follows. In most of the steps, design activities are added to the original design activities. Step A (learner analysis): An analysis of the learner’s digital literacy was added. This provides information about individual characteristics that affect task-technology fit. Step S (State standards and objectives): The addition of stating standards and objectives for digital literacy was included. Step S (Select methods, media, and materials): Instead of selecting methods and media, task analysis and decision-making regarding technology fit were included. For the task analysis, teachers first choose the instructional methods, and design a learning task which will be used according to the instructional method. After this, the activities are specified and sequenced. For the decision-making about the technology fit, technologies are mapped with the learning activities. Also, The selected technology is examined for its suitability in achieving digital literacy learning objectives. Step U (Utilize): Planning to prevent anticipated digital problems was added. Step R (Require learner participation): This step involves monitoring and solving technical problems and learner problems caused by technology use. Step E (Evaluate and revise): Evaluation of technology integration and task-technology fit was added. Three experts reviewed the validity of the revised model. The researchers of this study are now analyzing the expert review to modify the ASSURE-TTF model. 3.2. Expected outcomes After modifying the ASSURE-TTF model, a lesson plan will be developed by five elementary school teachers according to the instructional design model. Through these cognitive walkthrough methods, the usability of the model will be checked.
References
Agbu, J. F. (2015). Assessing technostress among open and distance learning practitioners: A comparative study. ASEAN Journal of Open Distance Learning, 7(1), 43-56. Daniela, L. (2019). Didatics of smart pedagogy: Smart pedagogy for technology enhanced learning. Springer. Eshet-Alkalai, Y. (2004). Digital literacy: a conceptual framework for survival skills in the digital era. Journal of Educational Multimedia and Hypermedia, 13(1), 93-106. European Commission (2020). Communication from the commission to the European parliament, the council, the European economic and social committee and the committee of the regions: Digital Education Action Plan 2021-2027 Resetting education and training for the digital age. Goodhue, D., & Thompson, R. L. (1995). Task–technology fit and individual performance. MIS Quarterly, 19(2), 213–236. Heinich, R.,Molenda,M., Russell, J. D., & Smaldino, S. (1999). Instructional media and technologies for learning (6th ed.). Merrill/Prentice Hall. Richey, R. C., & Klein, J. D. (2007). Design and development research. Taylor & Francis Group. Skulmowski, A., & Xu, K. M. (2022). Understanding cognitive load in digital and online learning: A new perspective on extraneous cognitive load. Educational Psychology Review, 34(1), 171-196. Kim, D., & Downey, S. (2016). Examining the Use of the ASSURE Model by K–12 Teachers. Computers in the Schools, 33(3), 153-168. Lemay, D. J., Bazelais, P., & Doleck, T. (2021). Transition to online learning during the COVID-19 pandemic. Computers in Human Behavior Reports, 4, 100130. Lei, G. (2023). Influence of ASSURE model in enhancing educational technology. Interactive Learning Environments, 1-17. Tang, C. M., & Chaw, L. Y. (2016). Digital Literacy: A Prerequisite for Effective Learning in a Blended Learning Environment?. Electronic Journal of E-learning, 14(1), 54-65. Ross, J., & Collier, A. (2016). Complexity, mess, and not-yetness: Teaching online with emerging technologies. In T. Anderson (Ed). Emergence and innovation in digital learning. (pp. 17-34). George Veletsianos.
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