Flowers 花繪攝影

The Relationship Between Motivation and Instructional Design

The relationship between motivation and instructional design is to include sets of strategies in systematic design activities to enhance learning motivation. According to Keller (1984), it is a rationalization in that we know that no matter how motivated learners are when they begin a course, it is not too difficult to bore them, if not kill their interest totally. Conversely, it is possible to stimulate or even inspire the students' desire to achieve. He also stated that motivation can be controlled by the appropriate application of rules and reinforcements. In his Development and Use of the ARCS Model of Instructional Design, he tried to confirm his assumption by examining these two specific questions. First, is it possible to synthesize the many concepts and theories of human motivation into a simple, meaningful model, or schema, that would be useful to a practitioner? Secondly, is it possible to develop a systematic, as opposed to the intuitive approach to designing motivating instruction? The ARCS Model has been developed and field-tested to explore these questions. Of course, the answer to both questions is yes.

The ARCS model includes a systematic design process to stimulate the motivation to learn. It is based upon expectancy-value theory (Tolman,1932; Lewin,1938). The expectancy-value theory assumes that people are motivated to engage in an activity if it is perceived to be linked to the satisfaction of personal needs, and if there is a positive expectancy for success.

The ARCS model defines four major categories, Attention, Relevance, Confidence, and Satisfaction, that has to be met for people to become and remain motivated. First, the model says that attention is a prerequisite for learning. However, in teaching, the real challenge is how to continue the attention of learners. The strategy to extend learners' attention is to use inquiry and participation. For example, using creativity techniques, problems solving activities, games, and role-playing in teaching. The second strategy is to make learning relevant. If students feel that what they are learning now is related to their current and future work, they will be more motivated. Examples such as to satisfy the need for affiliation and the need for achievement are good application techniques. The third strategy is to enhance learners' confidence because confidence can influence a student's persistence and sense of accomplishment. Some more detailed strategies include giving students clearly stated, appealing learning goals, providing self-evaluation tools, organizing materials on an increasing level of difficulty, attributing student success to effort, and allowing students opportunities to become increasingly independent in learning…etc. The last category or strategy is to make people feel good about their accomplishments and having a feeling of satisfaction. Some of these strategies are giving praise for successful progress, giving unexpected rewards, praising positive outcomes, avoiding negative influences and providing frequent reinforcements

             The ARCS model lists many practical techniques for instructors to enhance student confidence in learning. The model also shows that the motivation for learning can be enhanced through instructional skills. It mainly uses strategies to increase learners’ attention, relevance, confidence, and satisfaction. More importantly, these techniques can be systematically designed and incorporated into the learning process.

Reference

Keller, J. M. (n.d.). Development and use of the ARCS model of instructional design. Retrieved from https://link.springer.com/article/10.1007/BF02905780

Game-based Learning

There are many problems in the real world that need to be solved. Real-world problems are often more complicated than the problems we learn in school. The methods and techniques for students to solve problems in formal school settings are often well-designed, regular and procedural issues. These problems can be resolved by certain methods and steps provided by instructors, while the real-world problems have many uncertainties and irregularities. Interestingly, in the world of video gameplay, it is often possible to find the same situations, just like the real-world problems, without obvious steps and regularities to solve. While playing games, the gamer is solving problems as they are in the real world. The problems being solved are often limited by time and conditions and are not solved by applying a step-by-step solution as we learn at schools. Solving problems in video games and in a real-world are both processes of finding step-by-step solutions from irregularities. Video gameplay can more realistically reflect the real world's problem-solving skills. Therefore, game-based learning can be used as a learning tool at school to reflect real-world problems.

There is a gap in the kinds of problems being assessed and taught in schools and those desired in workplace environments (Shute & Emihovich, 2018). The field of game-based learning is trying to bridge the gap of problems between schools and workplace environments. According to Polya (1945), problem-solving is not an innate skill, but rather something that can be developed. Polya compared problem-solving skills to swimming, emphasizing it is a practical Skill. Since problem-solving skills can be learned after birth, and video gameplay can provide a real-world situation, game-based learning is an issue worthy of research, discussion, and application in formal education.

Games can teach us about learning. Recent research indicates problem-solving skills involve two facets: rule identification and rule application (Schweizer et al. 2013). Rule identification refers to the ability to acquire knowledge of the problem-solving environment, and rule application is the ability to control the environment by applying the knowledge acquired (Shute & Emihovich, 2018). In well-designed video games, game players often require identifying and applying rules. Take Use Your Brainz, a video game used to develop a stealth assessment of problem-solving skill, as an example, four-facet competency models have been included in the game, including analyzing givens and constraints, planning a solution pathway, using tools effectively and efficiently, and monitoring and evaluating progress. People who play games can discover the rules and apply what they have learned to become better at the game the more often they play it. This is the so-called practice makes perfect. Finding rules in games that seem to be irregular is what games can teach us about learning. In other words, the ability to solve problems will become stronger after learning by playing games.

           Playing and building games helps students understand complex systems—including their own systems of thinking (Farber, 2019). According to Farber, systems thinkers can “analyze how parts of a whole interact with each other to produce overall outcomes in complex systems.” He argues, that any game is a system. In traditional school learning, we constantly learn from parts without seeing the whole. However, game-based learning makes up for this deficiency, showing us the whole, and from there, we look for the tiny key parts that affect the whole problem. Isn't that the problem we see in the real world? Although there are many challenges in implementing game-based learning in formal education settings, it is still worth studying and discussing. Overall, it represents the mainstream of learning in the 21st century.

Reference

Shute, V. J., & Emihovich, B. (2018). Assessing Problem-Solving Skills in Game-Based Immersive Environments. Springer International Handbooks of Education Second Handbook of Information Technology in Primary and Secondary Education,635-648. doi:10.1007/978-3-319-71054-9_40

Farber, M. (2019, January 24). The Benefits of Constructionist Gaming. Retrieved from https://www.edutopia.org/article/benefits-constructionist-gaming