Badges are more than just participation trophies. Design them to commensurately represent the knowledge and skills gained.
While many institutions have used digital badges as an alternative way to recognize the skills and knowledge developed by students, some are also starting to use this approach in their in-house professional development programs – especially in faculty development programs.
By offering well-designed badges that accompany these programs, you can boost both participation and impact. Join us for this online training and learn how to design your badges to encourage deeper engagement that goes beyond “showing up”. Our instructor, Lindsay Doukopoulos, will share best practices for badging criteria at Auburn University, where 82% of participants chose to earn badges at annual professional development workshops.
indsay Doukopoulos Ph.D.
Assistant Director, Biggio Center for the Enhancement of Teaching and Learning, Auburn University
Lindsay’s teaching expertise includes experiential, active, and team-based learning in small and large lecture formats. Her research interests include instructional technologies and the use of digital artifacts (e.g., badging, ePortfolios, etc.) to assess and enhance integrated learning, gameful learning, and metacognition for students and faculty.
After a brief overview of our instructor’s faculty development badging program, we’ll walk through several badges Auburn has implemented for faculty. For each badge collection, we’ll address the following:
How was it designed, and what elements were considered in the design process?
What are the criteria for earning the badges? Why?
Who has earned the badges to date?
What impact did badge earners self-report?
What kind of data or artifacts did faculty submit to earn this badge / badge constellation? What did these show about how faculty were using what they learned?
We’ll close with a brief exercise that will let you start designing your own badge criteria for a program on your campus.
“Shifts in students’ learning style will prompt a shift to active construction of knowledge through mediated immersion.”-Chris Dede
The theory of constructivist-based learning, according to Dr. Seymour Papert, “is grounded in the idea that people learn by actively constructing new knowledge, rather than having information ‘poured’ into their heads.”
Moreover, constructionism asserts that people learn with particular effectiveness when they are engaged in constructing personally meaningful artifacts (such as computer programs, animations, 3D modeling, creating spatial environments in virtual reality or building robots).”
Technologies like virtual reality, especially for Gen Z students’, provides avenues that allow them to engage in a social, collaborative, and active learning environment.
Virtual reality, especially when combined with powerful storytelling, allows the student to participate in the story, develop empathy to experiences outside their current realm of understanding and allows them to be fully immersed in their own exploration and learning.
An interactive discussion on MOOCs, online learning, and the goal of 100 million learners by 2022
The Future Trends Forum welcomes
Anant Agarwal , the founder and CEO of edX, a non-profit venture created by Harvard University and the Massachusetts Institute of Technology, focused on transforming online and on-campus learning through groundbreaking methodologies.
He aims to help bring quality education to everyone, everywhere. Anant has also been a Professor of Electrical Engineering and Computer Science at MIT for 30 years.
This class will start with simple ways librarians may embed their skills remotely starting with the LMS especially through the use of portal tabs, blocks, eReserves, knowledge bases, and student/faculty orientations. We’ll then move on to discussing how to bring the traditional face-to-face BI session (which librarians know so well) into the online class through the use of team teaching, guest lecturing, and conducting synchronous workshops. We’ll explore in the 3rd week how the librarian can become more influential in online course design and development. The session concludes with an examination of the ways librarians can evaluate whether or not their virtual efforts are impacting student access to library resources as well as possible learning outcomes.
more on embedded librarianship in this iMS blog
Thirty students registered for Arizona State University Online’s general biology course are using ASU-supplied virtual reality (VR) headsets for a variety of required lab exercises
The VR equipment, which costs ASU $399 per student, allows learners to complete lab assignments in virtual space using goggles and a controller to maneuver around a simulated lab. Content for the online course was developed and assessed by ASU biology professors and was evaluated this summer. Students also can use their own VR headsets and access the content on their laptops, as 370 other students are doing.
A university official told Campus Technology the initiative will help online students have the experiences provided in brick-and-mortar labs as well as new ones that were impossible previously. The effort also will ease a problem on campus with limited lab space.
About half of colleges have space dedicated to VR, with adoption expected to increase as technology costs go down, according to a recent survey by nonprofit consortium Internet2. The survey found that 18% of institutions have “fully deployed” VR and are increasingly making it available to online students, while half are testing or have not yet deployed the technology.
Colleges are using VR for a variety of purposes, from classroom instruction to admissions recruiting to career training.
In addition, because the use of VR is growing in K–12 education, students will expect to use it in college.
Since the Open University was founded in 1984, more than 250,000 students have enrolled in courses. The Open University offers courses of study at the bachelor’s and master’s degree levels in cultural studies, education science, law, management, psychology, science and technology. Five of its master’s degree programs were top-ranked in 2017
Learning Tasks — concrete, authentic, whole task experiences that are provided to learners in order to promote schema construction for non-recurrent aspects and, to a certain degree, rule automation by compilation for recurrent aspects. Instructional methods primarily aim at induction, that is, constructing schemata through mindful abstraction from the concrete experiences that are provided by the learning tasks. Design steps:
Design learning tasks
Sequence task practice
Set performance objectives
Supportive Information — information that is supportive to the learning and performance of non-recurrent aspects of learning tasks. It provides the bridge between learners’ prior knowledge and the learning tasks. Instructional methods primarily aim at elaboration, that is, embellishing schemata by establishing nonarbitrary relationships between new elements and what learners already know. Design steps:
Design supportive information
Analyze cognitive strategies
Analyze mental models
JIT Information — information that is prerequisite to the learning and performance of recurrent aspects of learning tasks. Instructional methods primarily aim at compilation through restricted encoding, that is, embedding procedural information in rules. JIT information is not only relevant to learning tasks but also to Part-time practice. Design steps:
Design procedural information
Analyze cognitive rules
Analyze prerequisite knowledge
Part-task Practice — practice items that are provided to learners in order to promote rule automation for selected recurrent aspects of the whole complex skill. Instructional methods primarily aim at rule automation, including compilation and subsequent strengthening to reach a very high level of automatically. Design step:
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).
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).