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Why gamification is an effective approach to teaching and learning

Article: Why gamification is an effective approach to teaching and learning

Teaching/learning methods and gamification for student engagement

In the last few decades, many reform initiatives have shaped teaching and learning in different disciplines. Scholars argue that students should engage in learning that allows them to explore, inquire, solve problems, and think critically [Hmelo-Silver, Duncan & Chinn, 2007]. To this end, reform efforts within each of disciplines have focused on such strategies as inquiry learning, project-based learning, constructivist learning, problem-based learning and the integration of technology across all disciplines. Although these initiatives have different names, they share the common goal of engaging students through exploring real-world issues and solving practical problems.

Studies in recent years show that students who are engaged in their work are energized by four goals: success, curiosity, originality and satisfying relationships. Both, teachers and students, detest work that was repetitive, that required little or no thought, and that was forced on them by others. Engaging work is work that stimulates their curiosity, allows them to express their creativity and foster positive relationships with others. Students who are engaged exhibit three characteristics: (1) they are attracted to their work, (2) they persist in their work despite challenges and obstacles, and (3) they take visible delight in accomplishing their work. People who are engaged in their work are driven by four essential goals, each of which satisfies a particular human need: success, the need for mastery, curiosity, the need for understanding, originality, the need for self-expression and relationships, the need for involvement with others.

There is also a relationship between technology use and problem based learning (PBL) instruction. [Eskrootchi and Oskrochi 2010] that “students learn best by actively constructing knowledge from a combination of experience, interpretation and structured interactions with peers when using simulation in a PBL setting” (p. 243). This demonstrates that effectively implementing technology with PBL increases student achievement compared to students using technology alone. The researchers believe this is due to increased student collaboration, authenticity, and the establishment of spaces for more equitable contribution present in PBL-instructed classrooms.

From the emotional perspective, in order to provide to student’s higher doses of motivation and willingness to learn, innovative, digital and technological strategies for content provision should be applied. Technology-based learning approach based on gamification will be provided where technology and gamification will play a significant role in making learning more effective, efficient and enjoyable. Many different types of technology can be used to support and enhance learning with digital content (e.g. computer-supported collaborative learning systems, learning management systems, simulation modelling tools, educational games, web 2.0 social applications, 3D virtual reality, augmented reality and gamification and game design).

Multiple studies have reported that students in PBL-taught classrooms demonstrate improved critical-thinking and problem-solving skills. Researchers have also found that PBL is a successful way of teaching 21st-century skills, and that it increases student engagement and content learning. Further, students show more initiative by utilizing resources and revising work, behaviours that were uncharacteristic of them before they were immersed in the PBL-instructed classes [Barron et al. 1998].

Studies on motivation have found that students who are motivated by content learning and understanding are more likely to stay focused on school-related tasks than students motivated by task completion alone. Reward systems that are organized around engagement in a task and  cooperative learning also encourage learning. Thomas notes that PBL increases content mastery because it is organized around collaboration, authenticity, and student-driven inquiry. From the perspective of teachers, [Loucks- Horsely et al. 1998] identified 15 different strategies that are used for professional development for teachers which fall into five categories:

  1. Immersion: involve participants in doing science and mathematics
  2. Curriculum: curriculum strategies involve teachers with the actual learning materials they will use with their students
  3. Examining practice: that focuses on teachers own practice, job embedded learning
  4. Collaborative Work: professional networks and professional learning communities
  5. Vehicles mechanisms: structures of professional development primarily workshops and institutes

How gamification can be applied to the context of vocational education and training.

The design process: Design isn’t just art/illustration/creative expression but a general approach to attacking problems.

People like Roger Martin of the University of Toronto business school and David Kelley of Ideo argue this should be a process all businesses engage in for every purpose. We won’t go into all of the details, but it’s worth understanding its major principles so they can be applied to gamification.

Elements of “design thinking”

Purposive: It has a goal.

You’re not just trying to make something beautiful, or create a process that does certain things, but to achieve some objective and everything you do refers back to that objective.

Human-centred: It is the experience, stupid.

  • Everything should be based on the person coming up with solutions for people.
  • The experience is greater than the game element.

Balance of analytical and creative thinking: Not just a formula.

  • If you use just one or the other, your process can be too dry and formal, you won’t really address people’s experiential needs, and you miss out on lots of opportunities for creativity and innovation.
  • Focus on what to do when you’re “in the middle” there’s some data, but not enough to give us a clear, clean, structured algorithm.
  • Adductive reasoning inference from the best available explanation when information is insufficient.

Iterative : inherently expects to not get it right the first time

  • Try, fail, learn, and try again.
  • Prototyping and playtesting

 

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