Final Synthesis

As we are reaching the end of the course, I realize that it is modelled after a Learning for Use framework (Edelson, 2001).

  • Motivation: In Module A, we framed the issues around educational technology use in STEM. Through activities and discussion that targeted our underlying assumptions around technology, pedagogy, and STEM, our schema were activated and primed.
  • Knowledge Construction: In Module B, we examined foundational designs of TELEs. Our preconceptions were tested and we experimented with each of the designs. It was challenging to initially distinguish between these instructional frameworks, but it was possible through interaction and discussion.
  • Knowledge Refinement: In Module C, we explored emerging genres for teaching, learning, and digital technologies. Using these more current strategies, we re-visited how we could supplement TELEs to create more varied and rich learning experiences.

In this final synthesis post, I will analyze my learning in each module and how it has led me to my current ideas about teaching and learning STEM with technology.

Module A: Framing Issues

Reflecting upon what we have learned, my initial ideas about teaching and learning with technology can be enhanced.

A framework is needed for selecting, designing, and applying technology

After taking ETEC524, I started to used the SAMR and SECTIONS frameworks in this order:

  1. SAMR (Puentedura, 2017): If using a tool would only fall into the Substitution level, it should not be used. I took a rather reductionist approach towards using technology. I did not value tools that would be expensive to implement for a low return on learning. However, feedback from my ETEC524 instructor, Professor Boksic, made me question this strategy. She suggested that substitution shouldn’t be dismissed. I’ve spent two semesters thinking about this idea.
  2. SECTIONS (Bates, 2016): I love the SECTIONS framework because it considers many important variables. Ease of use and how the learning activity needs to be modified around the tool while maintaining a student centred experience is often overlooked.

The design of the experience needs to be based on learning theories

My personal learning theory colours my teaching and learning. I view learning as a journey through a landscape. The learner’s experiences are constructions of ideas that change as they interact with the landscape and others.

My previous teaching experiences forced me to prioritize limited time to explain concepts. Due to this, I developed a behaviourist and cognitivist bias. Although I appreciate constructivism, I do not think that everything needs to be socially constructed. I prefer scaffolding cycles of equilibrium and disequilibrium as per Piagetian theory (Yilmaz, 2011). Since students can develop misconceptions through assimilation, assessments and activities should specifically target these potential ideas and force students to confront them (Confrey, 1990). As students develop competence and confidence, the learning structure will fade from co-regulation to self-regulation.

With these perspectives, I find it valuable to explicitly structure learning based on preconceptions, scaffolding, and varied assessment.

Analysis of Assumptions

My original frameworks are missing explicit intersections with STEM. In re-reading my posts from Module A, I noticed many underlying assumptions about teaching and learning with technology that arise from my experiences of being a Chemistry student.

Teaching and learning was perceived as what the teacher did

Discussions focussed on what the teacher would do and how the teacher would structure the activity. If we weren’t talking about the teacher, we would be talking about how students interacted with content. We rarely discussed how students would interact with each other, the teacher, or others in a larger community. The peer and mentor interactions are important to STEM discourse and constructivism. By neglecting these topics initially, I realize that I had perceived high school math and science as independent learning tasks. Although this reflects how I learned as a student, it should not reflect how our students should be learning.

A hesitance towards technology

Many discussions were about student resistance and the lack of teacher training. Our class experienced barriers like limited time, access to technology, and challenges with implementation. Focussing on collaborative work and authentic assessment seemed like better options than to implement technology.

At the start of the semester, I had just observed the first half of the engineering design course I support. Many students hated our technology enhanced active learning exercises or felt that they did not know enough to participate. Although these feelings of learning may have been due to students overestimating their capabilities or experiencing a high cognitive load, it was difficult to convince students that active learning was helpful (Deslauriers et al, 2019). With my behaviourist and cognitivist bias, I was more interested in implementing pre-lecture quizzes in our learning management system. Since students did not appear to complete their readings, using marked assessments would be more motivating and lead to more compliance.

Teaching and learning occurs in an architecture of support

My implicit assumptions of teacher-centred learning, resistance to technology, and structuring learning for compliance reveal my dehumanization of learning. My behaviourist bias has caused me to perceive students as passive beings. This cynicism is problematic because it does not afford students opportunities for autonomy or exploration outside of pre-set constraints. The behaviourist mindset of punishment and reward also does not offer as many formative opportunities for students to learn from their mistakes.

Thankfully, the case study and interview with a colleague were important activities in re-humanizing teaching and learning. My interview transcript revealed that I was hyper-aware of the negative experiences and often used prompts about the challenges of using technology. Luckily my colleague brought a much more positive perspective to using technology. She reminded me that students do enjoy learning, technology can be motivating, and technology’s affordances can encourage participation. I realized that my reductionist bias to teaching and learning limited my appreciation of motivation, social learning, and other human factors.

While working in the unpacking assumptions discussion, I drew what could be an ideal science classroom.

I was reminded that the architecture of a space strongly impacts learning and collaboration. In this ideal space, one of the best pieces of technology would be the movable chairs and tables. Teachers, students, and the concepts being discussed can modify the space and how the interactions occur. I really like this space because it reflects the community aspect of scientific discourse, encourages collaboration, and makes learning visible.

With this paradigm shift, I was working towards determining how a pedagogical structure informs our choice of tools and how the affordances can be leveraged. Specifically, I wanted to explore how constructivist approaches could facilitate participatory learning.

Module B: Foundational designs of STEM TELEs

In Module B, I experienced a lot of initial confusion as I tried to differentiate between the TELEs. With the exception of Anchored Instruction, all the TELEs looked the same. After the synthesis discussion, I understood that the strategy for learning and locus of construction for each TELE is what makes them different.

TELE Strategy for Learning Locus of construction
Anchored Instruction Complex problem in an authentic narrative Teacher presents problem, students collaborate to solve it
SKI Scaffolding concepts Teacher; may transition to co-regulation and self-regulation
LfU Motivation for activity Student; prompt may be supplied by the teacher, students are motivated to fill in knowledge gaps
T-GEM Observation and analysis Student, teacher provides data, teacher may facilitate

The importance of distinct instructional frameworks

Through creating different activities using the TELEs and discussing my confusion with my classmates, I realized that the TELEs can supplement each other:

  • Anchored instruction contextualizes learning in an authentic situation. Students collaboratively solve complex problems by applying their prior knowledge (Cognition and Technology Group at Vanderbilt, 1992). This is important in showing students that STEM lives outside of a textbook and involves interdisciplinary connections.
  • SKI  is the most cognitivist of the TELEs we examined. It chunks concepts and encourages students to reflect, review, and reflect in order to make their learning visible (Linn et al, 2003). A SKI module can be a standalone activity for knowledge construction and can supplement a larger inquiry framework.
  • LfU supports teaching content and inquiry at the same time (Edelson, 2001). Its Piagetian parallels contextualize how activities will support learning.
  • T-GEM introduces novices to the inquiry cycle by generating a theory based on their prior knowledge, testing it, and modifying it (Khan, 2007). Classroom inquiry is challenging because there is an acceptable answer. The T-GEM framework can support the competing desires of getting students to engage in divergent thinking to generate their theory and then have them converge through evaluation and modification. Specifically targeting common misconceptions with test cases and outliers facilitates convergence to the accepted theories.

Large LfU cycles supported by SKI and T-GEM in the knowledge construction and refinement phases. The motivation could be supported by anchored instruction. These instructional frameworks are important in engaging in TPACK where teachers consider how the content can be represented, the pedagogical techniques that should be used, and how technology can support students and the concepts and activities (Mishra & Koehler, 2006).

The importance of grounding a TELE in learning theory

When creating a SKI module, I chose to use Articulate Rise because I found the WISE interface overwhelming. Rise is a fast authoring tool if you choose to play within its pre-defined blocks. In contrast, the WISE tool is more flexible and allows the user to design. Since I was so focused on the software, I had neglected the pedagogy of the lesson. Rise does not have a native open response option. Due to this, I have never considered creating a reflective journal task. I realized that the default affordances of a tool can trap the user into designing within these constraints.

This experience highlights the importance of TPACK. Teachers need to consider the intersections between technology, pedagogy, and the content in order to create a holistic learning experience (Mishra & Koehler, 2006). When I was trapped within Rise’s default affordances, I forgot the pedagogy and intentional design of a learning experience. Instead of thinking how a lesson can be molded to fit the technology, we should consider how a tool can be re-worked to for the learning experience. Now when I create Rise modules, I know that there is an inherent behaviourist bias due to the software. However, this will no longer limit my assessments to just recall and recognition questions. Instead, I can prompt users to pause, take notes, and re-visit their previous work.

Overall, Module B helped me appreciate the affordances of constructivist frameworks. The learning experience is more participatory and meaningful when students exercise more agency. The TELEs are instructional frameworks that are aligned STEM learning and support technology use.

Module C: Emerging genres of teaching, learning, and digital technologies

In Module C, we refined our understanding of instructional frameworks and TPACK by examining emerging genres.

Embodied Learning: Challenge the activities you create

I was surprised by Winn’s (2003) comments on how technology helps us expand our perception, but users are still physiologically constrained. Only after reading about the examples of how instructional misconceptions arose from time distortion and students taking visuals literally, did the concept of embodiment become more clear. Niebert et al (2012) emphasize that metaphors and analogies are effective when they are embodied. Metaphors and analogies fail when the source is constructed only by the teacher; students are not connecting to their knowledge landscapes and try to make sense of the metaphor based on their experiences. Metaphors can also fail when their use does not expand to all cases for the target domain.

In discussing how to divide by fractions, we were confused with how to use the sharing analogy. Sharing is a good analogy because it is embodied when you are working with whole numbers. Students can draw pictures or use manipulatives to show the actual sharing. However, this does not extend to cases where we try to divide by fractions. It is impossible to share a number of objects with a fraction of an individual. Instead, using the “how many groups of X are in Y” analogy is more effective. Although it is not as embodied as sharing, it extends well into more cases.

Knowledge Diffusion: Learning extends outside of the formal classroom

This lesson highlighted the nature of science and the conventions of the scientific community. Science education needs to reflect the personal construction of meaning based on independent interactions and observations and the social construction that is based on scientific discourse (Driver et al, 1994). Students need to appreciate both the empirical basis and the social construction and validation of science by engaging in activities that reflect this. Driver et al (1994) highlighted the importance of experts being able to switch between theories based on the context and what works. This idea aligns well with Piaget’s comments on accommodation where learners may accrete, tune, and accommodate (Yilmaz, 2011).

Given the need to participate in scientific discourse, informal learning helps students examine extra-curricular connections and develop their personal interests. The resources from Exploratorium looked like take home projects for students to get them excited about science in everyday life. The virtual field trips are also helpful in getting students an inside perspective of jobs and contexts they may not normally have access to. Although the virtual field trips seemed more like videos, it is important for students to engage in asynchronous or synchronous dialogue with these experts. STEM learning should not be confined to the formal classroom.

Information Visualization: Productive constraints can promote learning

As we are reaching the end of the course, I recognize that fully online learning and tools have a negative public perception. Face-to-face and real experiences are often more valued and consequently seen as inherently better. However, well-designed simulations can provide productive constraints that lead to larger learning gains (Finkelstein et al, 2005).

In creating my acid and base LfU lesson with a PhET simulation, I was initially hesitant in my PhET selection. When thinking about the potential instructional misconceptions that could arise, I thought that the PhET was not useful. It did not show dynamic equilibrium or solvent interactions. Again, I realized that I was focussed on a technology and content intersection and was forgetting about the pedagogy. The PhET simplifies the reality of dynamic equilibrium so that students interact within productive constraints; having too much content would lead to cognitive overload and students would end up watching rather than exploring (PhET Simulations, 2013). A standalone lesson does not need to be complete. Rather, it is an entry point for students to explore the content and it equips them with the skills to proceed to the next level. Like how LfU has a knowledge refinement phase and T-GEM has a modification phase, there needs to be activities for further learning. Learning is a cycle that continues so that students can continue to accommodate and refine their schema.

Next Steps

My teaching philosophy needs to better reflect how people learn in science. I can use the TPACK framework as the overarching lens:

  • Technology: Continue using the SAMR and SECTIONS modules for selecting, designing, and applying tools.
  • Pedagogy: Continue apply learning theories to create assessments. Instructional frameworks can support this.
  • Content: Personal construction and engagement in scientific discourse needs to be reflected in the classroom (Driver et al, 1994). To be scientifically literate, students need to engage in opportunities to develop the discipline’s symbolic system, observe phenomena, and participate in discourse through shared problems and tasks.

My experiences in teaching and learning have steered me away from the community aspects of learning science. When there is a time crunch, content is prioritized over collaboration and inquiry. Since I am no longer a classroom teacher, I cannot apply these new understandings in a chemistry context. My suggestions for what could occur in the classroom will stay as ideas. This was a challenge I always had when I participated in discussions: I don’t really know what it’s like in a real classroom. Never having access to a classroom has also caused me to focus more on content and technology.

To speak to my ideas at the beginning of this course, I’d like to address each of the misconceptions I had:

  • Students are resistant to active learning, maybe we should use it less: Students are novices, they may be overestimating their understanding and misinterpreting the increased cognitive load as not learning (Deslauriers et al, 2019). We need to address their feelings of learning because their frustrations may translate to limited self regulation for learning. The benefits and realities of active learning need to be shared with students (Deslauriers et al, 2019). We can also support students by creating structured pre-lecture tasks to build their confidence and engage in knowledge construction. Especially in first year university courses, these tasks can model the expectations for lecture preparation and orient students to active learning. Facilitated in-person activities should support knowledge refinement.
  • If using a technology results in substitution, it shouldn’t be used: Substitution shouldn’t be dismissed. A substitution may have overhead costs, but a reductionist perspective ignores the impact on the feeling of learning. The emotions and fun aspects can be motivating. As well, substitution may link towards multiple representations which can connect to diverse groups of students.
  • Before transitioning to constructivist methods, learning needs to be scaffolded: This is not necessarily true. In the TELEs we examined, the strategy for learning and locus of construction lead to different experiences. To motivate learning, students need to experience disequilibrium. To make their learning visible, their misconceptions need to be challenged and their prior knowledge needs to be tested.

I can apply my new understandings in instructional design for the engineering course I support and the medicine e-modules I work on. Although I do not have the content knowledge, participating in a community of inquiry with my team members will help fill the gaps. I look forward to making recommendations about learning objects and learning experiences. I will not have access to modifying physical spaces, but I can still shape a digital space so that it has an architecture of support and collaboration.

To support this digital architecture, I want to learn more about user experience and designing for accessible experiences. Next semester, I am taking Text Technologies: The Changing Spaces of Reading and Writing and Ableism, Equity, and Educational Technology. I think these courses will help me further explore these areas. By exploring the TELEs, examples of authentic assessments, and the larger scientific discourse, I think it’s important to explore multiple representations of content and multiple methods of communication. Our spaces are often dominated by text but multimedia is often more engaging. The challenge with multimedia is that it should also be presented with alt text or transcripts. However, this is an accessibility requirement and should be built into the design process. With these new questions and areas of interest, the Learning for Use cycle begins again.

References

Bates, T. (2016). Teaching in a digital age. Retrieved from https://opentextbc.ca/teachinginadigitalage/part/9-pedagogical-differences-between-media/

Cognition and Technology Group at Vanderbilt (1992). The Jasper series as an example of anchored instruction: Theory, program, description, and assessment data. Educational Psychologist, 27(3), 291-315.

Confrey, J. (1990). A review of the research on student conceptions in mathematics, science, and programming. Review of research in education, 16, 3-56.

Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences of the United States of America, 116(39), 19251-19257. doi:10.1073/pnas.1821936116

Driver, R., Asoko, H., Leach, J., Scott, P., & Mortimer, E. (1994). Constructing scientific knowledge in the classroom. Educational researcher, 23(7), 5-12.

Edelson, D.C. (2001). Learning-for-use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching,38(3), 355-385.

Finkelstein, N.D., Perkins, K.K., Adams, W., Kohl, P., & Podolefsky, N. (2005). When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment. Physics Education Research,1(1), 1-8.

Khan, S. (2007). Model-based inquiries in chemistry. Science Education, 91(6), 877-905.

Linn, M., Clark, D., & Slotta, J. (2003). Wise design for knowledge integration. Science Education, 87(4), 517-538.

Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. The Teachers College Record, 108(6), 1017-1054.

Niebert, K., Marsch, S., & Treagust, D. F. (2012). Understanding needs embodiment: A theory‐guided reanalysis of the role of metaphors and analogies in understanding science. Science Education, 96(5), 849-877. doi: 10.1002/sce.21026

[PhET Simulations]. (2013, Jan 12). PhET: Research and Development [Video file]. Retrieved from https://youtu.be/qdeHagIeyrc

(2017, Oct 28). Ruben Puentedura – Rethinking Educational Technology [Video file]. Retrieved from https://youtu.be/7N67bt0FA8s

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.

Yilmaz, K. (2011). The cognitive perspective on learning: Its theoretical underpinnings and implications for classroom practices. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 84(5), 204-212. doi:10.1080/00098655.2011.568989

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