Co-learning, Co-teaching, and Cogenerative Dialogues to Improve Learning and Teaching Outcomes

What happens when you allow two people with seemingly different backgrounds to work together?  Great collaboration! This is true of a program co-sponsored by the Center for Educational Equity and Big Brother/ Big Sister that paired 9-14 year old girls with adult women to learn about computers.  The little and big sisters would meet to solve computer problems through a software program called SISCOM, (Wolman, 1986). Together they would dive deep into discussion, take turns leading and learning, helping each other problem solve through a process that provided 20 hours of computer basics instruction, (Wolman, 1986). Not only did the pairs work together to solve their shared problem but institutions worked together to provide the necessary resources.  This story highlights the successes of Co-Learning.

Traditional learning environments are generally set up to rely on one “expert” or teacher to lead and the remaining participants as the learners.  The teacher chooses what material to cover and to what extent the participants engage in the material. While this system works on the surface level, one of the major problems is that the teacher and students do not interact,“…when teachers and students do not interact successfully, contradictions occur,” (Tobin & Roth, 2005). This leads to the development of negative emotions that can manifest as disinterest, disappointment, frustration for the students, and job dissatisfaction for the teachers, (Tobin & Roth, 2005). According to Rheingold, one of the appeals of co-learning is that it levels out the hierarchy of the classroom.  When Rheingold engages in co-learning, he has everyone sit in a circle because then everyone is visible and everyone has an equal voice, (Rheingold, 2018). Co-learning assumes that teacher isn’t the gatekeeper nor the expert in all subjects and that all participants have something valuable to share and teach about a given concept. Just like in the Big Brother/Big Sister example above, neither the little nor big sister had an advantage over the learning and teaching of the SISCOM program. Both partners took equal interest and value in what the other knew, shared, and did. Because of the flattened hierarchy, it increased motivation, engagement, and excitement about learning/teaching, thereby improving learning outcome and attitudes towards learning, (Tobin, 2014).

One of the coveats of co-learning is co-teaching. While co-learning gives all participants an equal voice in learning together, co-teaching takes this a step further by inviting participants to also engage in all phases of the teaching process, (Tobin and Roth, 2005).  When implemented, co-teaching occurs between two or more teachers where one teacher may take on a mentor role. The most important factor of co-teaching is that it is not a mere division of tasks, but rather that teachers participate in the creation of all tasks.  Because some of the learning that occurs is subconscious, following through on process of co-teaching is important, (Tobin & Roth, 2005).

Diagram of the Co-teaching summary
Figure 1.1 Co-Teaching Summary

I’d also like to make a small mention about cogenerative dialogues. Tobin defines cogenerative dialogues as a side-component of co-teaching though it may also be used seperately.  Cogenerative dialogues involves small groups of about 5 individuals representing stakeholders (or demographics) that discuss specific incidences in class including reflection on lessons, (Tobin, 2014). Initially, these discussions can explore what works and what doesn’t in class lessons, but the discussions can also be expanded to roles of students/teachers, classroom rules, and how to use resources, (Tobin, 2014).  The benefit of these independent discussions that that all views and understandings are valued and all explanations are co-generated. It helps to ease communications among all cultural, socioeconomic boundaries by identifying (and acting upon) contradictions and later improving the quality of teaching and learning (Tobin & Roth, 2005).

Diagram of summary of cogenerative dialogue theory
Figure 1.2 Summary of Cogenerative Dialogue Theory

Despite the benefits of co-learning, several barriers should be addressed. Rheingold hypothesizes that teachers may be adverse to adopting co-learning because of the high level of trial and error that goes along with it, (Rheingold, 2018).  Teachers must give up a certain level of control and understand that outcomes will vary from classroom to classroom. While Rheingold is sympathetic to these barriers, he argues that trial and error also offers real-time modeling of problem solving and troubleshooting.  The key is to show students how to reflect upon a problem, re-examine, and adjust to the situation as necessary, (Rheingold, 2018).

Co-learning with a tech twist.  The ISTE standard for educators (4b in particular) indicates that teachers “collaborate and co-learn with students to discover and use new digital resources and diagnose and troubleshoot technology issues”, (ISTE, 2017).  In short, the standard places importance on the principles of co-learning addressed by Tobin and Roth, in addition to the modeling Rheingold stresses as a key factor to co-learning by focusing on how technology can foster collaboration while improving troubleshooting skills.  I had a particular problem in mind when I chose to explore this ISTE standard 4 component.  In my human nutrition class, students conduct a dietary analysis on their own diet.  The main features of this assignment is that students must accurately track their intake over the course of three days then input the data into an analysis program, later analyzing the findings in comparison to the Dietary Guidelines for Americans. The analysis program I had selected for this assignment, SuperTracker (https://www.supertracker.usda.gov/), will be discontinued at the end of this academic year for undisclosed reasons.  While the program was not without its faults, I supported the use of SuperTracker due to the fact that it is a free program easily accessible to anyone with internet, and it relied on the USDA database, an accurate and reliable set of nutrition data. I am now facing the challenge of reviewing apps and websites for SuperTracker’s replacement. However, the assignment would take a whole new meaning for students if they were allowed to co-learn from the start to finish of this project. In order for this project idea to be successful, it is important to consider how  nutrition-related apps can be leveraged to facilitate co-learning among students and professors regarding modes of nutrition education.

Addressing the ISTE Standard. As I started my search of nutrition-related apps and their feasibility for co-learning, I determined that credibility of app information should be a top priority. One of the challenges my students face is finding credible information to further their understanding.  For as long as I’ve been a professor, we’ve always looked at articles and websites and discussed the importance of reviewing these for credibility. However, information is now found in a variety of different mediums not limited to digital articles. Students are now using apps, videos, and other multimedia to gather information.  Understanding where that medium sourced their information is key to determining credibility. By examining and evaluating credibility for each app, all members involved in the use of this app would participate in troubleshooting and problem solving, a key caveat of the ISTE standard.

 The sheer amount of nutrition apps is staggering so I decided to narrow my search by starting with a credible source that provided a curated list, the Apps Review section of the Food and Nutrition Magazine. Food and Nutrition Magazine is a publication of the Academy of Nutrition and Dietetics (AND).  Where AND publishes research through the Journal of Nutrition and Dietetics, the magazine is often viewed as the “lighter” side or the “practical” side of the dietetics world. Food and Nutrition Magazine features new products, recipes, research highlights, in short, ways to keep updated in the food and nutrition world. The curated list of apps (https://foodandnutrition.org/tag/apps/) contains reviews of new and upcoming apps by the editors.  Those that are deemed reliable, credible, and useful, make the app list. The apps featured on the list explore a variety of nutrition topics that may have a nutrition education focus including food safety, physical activity, dining out, meal planning, in addition to apps that may be used by professionals in a variety of different capacities, such as video recording.

The list could serve as a good starting point for facilitating co-learning of the human nutrition dietary analysis project.  Having students further explore these apps in pairs (or small groups of three) in relation to assignment parameters can help facilitate collaboration and co-learning.  Adding a presentation element where these pairs teach the class on the usability of their chosen app may invoke the principles of co-learning. Finally, placing students in small, diverse groups and allowing them to reflect on the assignment makes their viewpoints heard as they embark in cogenerative dialogues.

While I initially had my sights set on this curated list for my human nutrition class, some of these apps may help facilitate student-professor collaboration, while others help foster practitioner-patient collaboration, making the possibility for implementing this list in other co-learning scenarios very feasible.  When both parties are able to contribute to how and why an app is used for various purposes, the co-learning is maximized.

References

ISTE. (2017).  ISTE standards for educators. Available at: https://www.iste.org/standards/for-educators

Rheingold, H. (2018). Co-learning: Modeling cooperative-collaborative learning [blog]. Available at: https://dmlcentral.net/co-learning-modeling-cooperative-collaborative-learning/

Tobin, K. (2014). Twenty questions about cogenerative dialogues. In book: Transforming urban education: Collaborating to produce success in science, mathematics and technology education, Chapter 11, Publisher: Sense Netherlands, Editors: Kenneth Tobin, Ashraf Shady, pgs.181-190 DOI: 10.1007/978-94-6209-563-2_11

Tobin, K., Roth, W.M. (2005). Implementing coteaching and cogenerative dialoguing in urban science education. School of Science and Mathematics, 105 (5): 313-21.

Wolman, J. (1986). Co-learning about computers. Educational Leadership, 43 (6), pg. 42. 

Building Computational Thinking through a Gamified Classroom

Who says playing video games doesn’t teach you anything?  Playing and creating games could actually help students develop another 21st century skill, computational thinking (CT).  Computational thinking is  a form of problem solving that takes large, complex problems, breaks them down into smaller problems, and uses technology to help derive solution. In deriving solutions, students engage in a systematic form of problem solving that involves four steps: 1) “decomposition” where a complex problem is broken down into smaller, more manageable problems, 2) “pattern recognition” or making predictions by finding similarities and differences between the broken down components, 3) “abstraction” developing general principles for the patterns that emerge, and  4) “algorithm design”, creating step-by-step instructions to solve not only this problem but other similar problems in the future, (Google School, 2016). By engaging in computational thinking, “students develop and employ strategies for understanding and solving problems in ways that leverage the power of technological methods to develop and test solutions, (ISTE, 2017).  In other words, the key to successfully following this process is that students develop their own models rather than simply applied existing models, (Google School, 2016).

Figure 1.1 Components of Computational Thinking
Figure 1.1 Components of Computational Thinking

In researching ways to apply computational thinking in the classroom, I ran across scholarly articles discussing the gamified classroom. I have always been intrigued with this concept, from my own experience students are so much more engaged during class time when the required content is converted into a game.  During these game sessions, my role changes from the the person delivering the content, to the person delivering the game (i.e. asking the questions).  The students are responsible for providing the content by providing solutions to the posed questions, thereby evoking problem-solving skills and in some cases, critical thinking skills. This idea-thread then led me to think “what are some ways that a “gamified” classroom can help develop computational thinking?”

To help answer my question, I came across two articles that pinpointed models in game-design to build computational thinking:

Article 1: Yang & Chang, 2013. Empowering students through digital game authorship: Enhancing concentration, critical thinking, and academic achievement.

Yang and Chang explore how students can increase their motivation for learning when they are allowed to design their own game given a specific topic.  During the game design process there is significant problem-solving that occurs because of the interaction and the immediate feedback the process entails.  In addition, students gain high order thinking such as building creativity, and critical thinking. The authors mention three game building software that does not require extensive coding skills: RPG Maker, Game Maker, and Scratch. During their study, the researchers investigated the effects of game design process on seventh grade biology students that were using either Flash animation (digital flash cards)  or RPG Maker.  The investigated effects included concentration, critical thinking, and academic performance. Their result demonstrated that the group using the RPG maker had significant improvements on critical thinking and academic performance, while no significant difference was noted on concentration for both groups.

Article 2: Kazimoglu, et. al., 2012.  A serious game for developing computational thinking and learning introductory computer programming.

Kazimoglu et. al. begin their inquiry by providing a few definitions.  It is important to understand the terminology they use, mainly defining any game used for educational purposes as a “serious” game.  They acknowledge that several definitions of computational thinking exist so they create their own definition that require the following elements: 1) conditional logic (true vs. false conditions); 2) building algorithms (step-by-step instructions); 3) debugging (resolving issues with the instructions); 4) simulation (modeling); and 5) distributed computation (social sharing). The authors are challenged to create a non-threatening introduction to programming unit to combat common student perception that programming is “difficult.” Kazimoglu et. al. believe that when students are allowed to engage in game design, they are motivated to learn which provokes problem solving. They take this approach to their introduction programming class where they challenge students through a series of exercises using the Robocode platform. At the end of the study, all students successfully completed the exercise, engaging in problem-solving skills.

Conclusions. Interestingly, both of these articles struggle to exactly define “computational thinking” and both mention that specific research investigating the extent to which games can develop CT is lacking.  However, what both can agree on is that CT is best developed when students are the game designers.  In order to do this, both studies involved elements of programming instruction to help students successfully build their games.

While these articles offer models into successfully implementing computational thinking through game design and creation, it was a little disheartening to discover that programming instruction was a necessary component. My inclination was to think how can these processes be implemented and/or adapted in other classroom scenarios particularly when programming instruction may or may not be feasible.  Interestingly, not all researchers agree that programming need be involved in successful CT implementation. Voogt et. al. argue that although most research on CT involves programming, because CT is a thinking skill,  it does not require programming in order to be successfully implemented, (Voogt et. al., 2015). In fact, in a literature review conducted by Voogt demonstrated that students do not automatically transfer CT skills to a non-programming context when instruction focused on programming alone. The strongest indicator of CT mastery was actually heavily dependant on instructional practices that focuses on application, (Voogt et. al., 2015).

The lack of a standard definition of computational thinking also needs to be addressed. The two articles above and the Voogt researchers agree that discrepancies exist among current definitions of computational thinking.  To avoid confusion regarding the role of programming and other such technologies, computational thinking can be simply defined as a way of processing information and tasks to solve complex problems, (Voogt et. al., 2015).  It is a way to look at similarities and relationships between a problem and follow a systematic process to reaching a solution.  Figure 1.2 summarizes this simplified process.

Figure 1.2 Simplified Computational Thinking Components
Figure 1.2 Simplified Computational Thinking Components

According to this new context, it is not necessary to program games in order for students to build computational thinking.  Allowing students to participate in systematic artifact creation will do the trick.  Some examples of artifact creation without the use of programing include: remixing music, generating animations, developing websites, and writing programs.  The main idea of this artifact creation process is that students follow procedures that can be applied to similar problems. Figure 1.3 highlights this artifact creation process.

Figure 1.3 Artifact Creation Process for Computational Thinking
Figure 1.3 Artifact Creation Process for Computational Thinking

How can this artifact creation process be used in creating gamified classroom?  To help me explore this issue, one of my colleagues suggested allowing students to develop and design their own board game. While the solution seems low-tech, others agree with this strategy.  Michele Haiken, an educational leadership for ISTE, writes about adapting “old school” games for the classroom to help develop critical thinking and problem solving skills, (Haiken, 2017).  Students can even create an online “quest,” scavenger hunt, or create a “boss event” to problem-solve computationally, (Haiken, 2017).  For more tech-y solutions, existing platforms and/or games such as GradeCraft and 3DGameLab can be used to  apply computational thinking in a gamified classroom, (Kolb, 2015). Regardless of the method used, low-tech board games or high-tech game creation through programming, allowing students to participate in the artifact creation process helps to build computational skills that they can then apply to other complex problems to create their own models.

References

Google School, (2016). What is computational thinking? [Youtube Video]. Retrieved from: https://www.youtube.com/watch?v=GJKzkVZcozc&feature=youtu.be.

Haiken, M., (2017).  5 ways to gamify your classroom. Retrieved from: https://www.iste.org/explore/articledetail?articleid=884.

International Society for Technology in Education, (2017).  The ISTE standards for students. Retrieved from: https://www.iste.org/standards/for-students.

Kazimoglu, C., et. al., (2012). A serious game for developing computational thinking and learning introductory computer programming. Procedia-Social and Behavioral Sciences, 47, 1991-1999.

Kolb, L., (2015). Epic fail or win? Gamifying learning in my classroom. Retrived from: https://www.edutopia.org/blog/epic-fail-win-gamifying-learning-liz-kolb.

Voogt J, et. al., (2015). Computational thinking in compulsory education: Toward an agenda for research and practice. Education and Technologies, 20(4), 715-728.

Yang, Y. C., & Chang, C. (2013). Empowering students through digital game authorship: Enhancing concentration, critical thinking, and academic achievement. Computers & Education, 68(c), 334–344.