Technology Acceptance Model (TAM) is the most widely used theoretical framework that looks at technology acceptance and there have been different iterations of the basic model (Fig 3). The two main variables that TAM incorporates are Perceived usefulness and Perceived ease of use (Davis ,1989). The Technology acceptance model was developed in order to identify the user’s intention and bias to use a particular technology based upon its qualities of usefulness and ease of use
The survey was based on the Technology Acceptance Model and contained questions that were modified but previously used in other questionnaires. Technology Acceptance questionnaires contain questions on Perceived Ease of Use (PEU) and Perceived Usability (PU) of the technology as well as the Intent to Use (IU) it later on. For the question “I think I would like to use Augmented Reality in my designs frequently” while 45% agreed or strongly agreed, 45% either disagreed or strongly disagreed.
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More on Technology Acceptance Model in this blog https://blog.stcloudstate.edu/ims?s=Technology+acceptance+model
College students’ perceptions of pleasure in learning – Designing gameful gamification in education
investigate behavioral and psychological metrics that could affect learner perceptions of technology
today’s learners spend extensive time and effort posting and commenting in social media and playing video games
Creating pleasurable learning experiences for learners can improve learner engagement.
uses game-design elements in non-gaming environments with the purpose of motivating users to behave in a certain direction (Deterding et al., 2011)
How can we facilitate the gamefulness of gamification?
Most gamified activities include three basic parts: “goal-focused activity, reward mechanisms, and progress tracking” (Glover, 2013, p. 2000).
gamification works similarly to the instructional methods in education – clear learning and teaching objectives, meaningful learning activities, and assessment methods that are aligned with the objectives
the design of seven game elements:
Storytelling: It provides the rules of the gamified activities. A good gamified activity should have a clear and simple storyboard to direct learners to achieve the goals. This game-design element works like the guidelines and directions of an instructional activity in class.
Levels: A gamified activity usually consists of different levels for learners to advance through. At each level, learners will face different challenges. These levels and challenges can be viewed as the specific learning objectives/competencies for learners to accomplish.
Points: Points pertain to the progress-tracking element because learners can gain points when they complete the quests.
Leaderboard: This element provides a reward mechanism that shows which learners are leading in the gamified activities. This element is very controversial when gamification is used in educational contexts because some empirical evidence shows that a leaderboard is effective only for users who are aggressive and hardcore players (Hamari, Koivisto, & Sarsa, 2014).
Badges: These serve as milestones to resemble the rewards that learners have achieved when they complete certain quests. This element works as the extrinsic motivation for learners (Kapp, 2012).
Feedback: A well-designed gamification interface should provide learners with timely feedback in order to help them to stay on the right track.
Progress: A progress-tracking bar should appear in the learner profile to remind learners of how many quests remain and how many quests they have completed.
Dominguez et al. (2013) suggested that gamification fosters high-order thinking, such as problem-solving skills, rather than factual knowledge. Critical thinking, which is commonly assessed in social science majors, is also a form of higher-order thinking.
Davis (1989) developed technology acceptance model (TAM) to help people understand how users perceive technologies. Pleasure, arousal, and dominance (PAD) emotional-state model that developed by Mehrabian (1995) is one of the fundamental design frameworks for scale development in understanding user perceptions of user-system interactions.
Van der Heijdedn (2004) asserted that pleasurable experiences encouraged users to use the system for a longer period of time Self-determination theory (Deci & Ryan, 1985) has been integrated into the design of gamification and addressed the balance between learners’ extrinsic and intrinsic motivation.
Ryan and Deci (2000) concluded that extrinsic rewards might suppress learners’ intrinsic motivation. Exploiting the playfulness and gamefulness in gamification, therefore, becomes extremely important, as it would employ the most effective approaches to engage learners.
Sweetser and Wyeth (2005) developed GameFlow as an evaluation model to measure player enjoyment in games
Fu, Su, and Yu (2009) adapted this scale to EGameFlow in order to measure college students’ enjoyment of e-learning games. EGameFlow is a multidimensional scale that consists of self-evaluated emotions.
Eppmann, Bekk, and Klein (2018) developed gameful experience scale (GAMEX) to measure gameful experiences for gamification contexts. one of the limitations of GAMEX to be used in education is that its effects on learning outcome has not been studied
the Big Five Model, which has been proposed as trait theory by McCrae & Costa (1989) and is widely accepted in the field, to measure the linkages between the game mechanics in gamification and the influences of different personality traits.
Storytelling in the subscale of Preferences for Instruction emphasizes the rules of the gamified learning environments, such as the syllabus of the course, the rubrics for the assignments, and the directions for tasks. Storytelling in the subscale of Preferences for Instructors’ Teaching Style focuses on the ways in which instructors present the content. For example, instructors could use multimedia resources to present their instructional materials. Storytelling in the subscale of Preferences for Learning Effectiveness emphasizes scaffolding materials for the learners, such as providing background information for newly introduced topics.
The effective use of badges would include three main elements: signifier, completion logic, and rewards (Hamari & Eranti, 2011). A useful badge needs clear goal-setting and prompt feedback. Therefore, badges correlate closely with the design of storytelling (rules) and feedback, which are the key game design elements in the subscale of Preferences for Instruction.
Students can use Google to search on their laptops or tablets in class when instructors introduce new concepts. By reading the reviews and viewing the numbers of “thumbs-up” (agreements by other users), students are able to select the best answers. Today’s learners also “tweet” on social media to share educational videos and news with their classmates and instructors. Well-designed gamified learning environments could increase pleasure in learning by allowing students to use familiar computing experiences in learning environments.
Arshad, M., & Akram, M. S. (2018). Social Media Adoption by the Academic Community: Theoretical Insights and Empirical Evidence From Developing Countries. The International Review of Research in Open and Distributed Learning, 19(3). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/3500
Building on the social constructivist paradigm and technology acceptance model, we propose a conceptual model to assess social media adoption in academia by incorporating collaboration, communication, and resource sharing as predictors of social media adoption, whereas perceived ease of use and perceived usefulness act as mediators in this relationship.
According to the latest social media statistics, there are more than 2 billion Facebook users, more than 300 million Twitter users, more than 500 million Google+ users, and more than 400 million LinkedIn users (InternetLiveStats, 2018).
although social media is rapidly penetrating into the society, there is no consensus in the literature on the drivers of social media adoption in an academic context. Moreover, it is not clear how social media can impact academic performance.
Social media platforms have significant capability to support the social constructivist paradigm that promotes collaborative learning (Vygotsky, 1978).
Perceived usefulness (PU) – This was defined by Fred Davis as “the degree to which a person believes that using a particular system would enhance his or her job performance“.
Perceived ease-of-use (PEOU) – Davis defined this as “the degree to which a person believes that using a particular system would be free from effort” (Davis 1989).
proposing a Social Media Adoption Model (SMAM) for the academic community
Social media platforms provide an easy alternative, to the academic community, as compared to official communications such as email and blackboard. my note: this has been established as long as back as in 2006 – https://www.chronicle.com/article/E-Mail-is-for-Old-People/4169. Around the time, when SCSU announced email as the “formal mode of communication).Thus, it is emerging as a new communication and collaboration tool among the academic community in higher education institutions (Roblyer, McDaniel, Webb, Herman, & Witty, 2010). Social media has greatly changed the communication/feedback environment by introducing technologies that have modified the educational perspective of learning and interacting (Prensky, 2001).
the Theory of Reasoned Action (Fishbein & Ajzen, 1975) and the Technology Acceptance Model (Davis, 1989) have been used to assess individuals’ acceptance and use of technology. According to the Technology Acceptance Model, perceived usefulness and perceived ease are the main determinants of an individual’s behavioral intentions and actual usage (Davis, 1989).
Perceived usefulness, derived from the Technology Acceptance Model (TAM), is the particular level that an individual perceives that they can improve their job performance or create ease in attaining the targeted goals by using an information system. It is also believed to make an individual free from mental pressure (Davis, 1989).
Perceived ease of use can be defined as the level to which an individual believes that using a specific system will make a task easier (Gruzd, Staves, & Wilk, 2012) and will reduce mental exertion (Davis, 1989). Venkatesh (2000) posits this construct as a vital element in determining a user’s behavior toward technology. Though generally, there is consensus on the positive effect of perceived ease of use and perceived usefulness on users’ attitude towards social media, it is not yet clear which one of these is more relevant in explaining users’ attitude towards social media in the academic community (Lowry, 2002). Perceived ease of use is one of the eminent behavioral beliefs affecting the users’ intention toward technology acceptance (Lu et al., 2005). The literature suggests that perceived ease of use of technology develops a positive attitude toward its usage (Davis, 1989).
Collaborative learning is considered as an essential instructional method as it assists in overcoming the communication gap among the academic community (Bernard, Rubalcava, & St-Pierre, 2000). The academic community utilizes various social media platforms with the intention to socialize and communicate with others and to share common interests (Sánchez et al., 2014; Sobaih et al., 2016). The exchange of information through social media platforms help the academic community to develop an easy and effective communication among classmates and colleagues (Kaplan & Haenlein, 2010). Social media platforms can also help in developing communities of practice that may help improve collaboration and communication among members of the community (Sánchez et al., 2014). Evidence from previous work confirms that social media platforms are beneficial to college and university students for education purposes (Forkosh-Baruch & Hershkovitz, 2012). Due to the intrinsic ease of use and usefulness of social media, academics are regularly using information and communication technologies, especially social media, for collaboration with colleagues in one way or the other (Koh & Lim, 2012; Wang, 2010).
IM 690 lab plan for March 3, MC 205: Oculus Go and Quest
Readings:
TAM:Technology Acceptances Model
Read Venkatesh, and Davis and sum up the importance of their model for instructional designers working with VR technologies and creating materials for users of VR technologies.
UTAUT: using the theory to learn well with VR and to design good acceptance model for endusers: https://blog.stcloudstate.edu/ims/2020/02/20/utaut/
Watch both parts of Victoria Bolotina presentation at the Global VR conference. How is she applying UTAUT for her research?
Read Bracq et al (2019); how do they apply UTAUT for their VR nursing training?
joining a space and collaborating and communicating with other users
Assignment: Group work
Find one F2F and one online peer to form a group.
Based on the questions/directions before you started watching the videos:
– Does this particular technology fit in the instructional design (ID) frames and theories covered
– how does this particular technology fit in the instructional design (ID) frames and theories covered so far?
– what models and ideas from the videos you will see seem possible to be replicated by you?
exchange thoughts with your peers and make a plan to create similar educational product
Post your writing in the following D2L Discussions thread
Augmented Reality with Hololens Watch videos at computer station)
Unified Theory of Acceptance and Use of Technology (UTAUT)
and Technology Acceptances Model (TAM)
Bracq, M et al (2019). Learning procedural skills with a virtual reality simulator: An acceptability study. Nurse Education Today, 79, 153–160. https://doi.org/10.1016/j.nedt.2019.05.026
continued practice, clear goals and immediate feedback
project-based learning, Minecraft and SimCity EDU
Gamification of learning versus learning with games
organizations to promote gaming and gamification in education (p. 6 http://scsu.mn/1F008Re)
the “chocolate-covered broccoli” problem
Discussion: why gaming and gamification is not accepted in a higher rate? what are the hurdles to enable greater faster acceptance? What do you think, you can do to accelerate this process?
Gaming in an academic library
why the academic library? sandbox for experimentation
the connection between digital literacy and gaming and gamificiation
Gilchrist and Zald’s model for instruction design through assessment
Discussion: based on the example (http://web.stcloudstate.edu/pmiltenoff/bi/), how do you see transforming academic library services to meet the demands of 21st century education?
Gaming, gamification and assessment (badges)
inability of current assessments to evaluate games as part of the learning process
“microcredentialing” through digital badges
Mozilla Open Badges and Badgestack
leaderboards
Discussion: How do you see a transition from the traditional assessment to a new and more flexible academic assessment?
