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

Remote Emergency Teaching

EDUCAUSE has a great article on the differences between emergency remote teaching and online learning. The COVID-19 situation has caused a mass online migration for academic continuity. However, as argued in the article, this situation is emergency remote teaching, rather than online learning.

In ETEC524, everyone created a blended or fully online unit of learning within a course. As part of this project, we explored how to do this by using frameworks to select, design, and apply learning technologies and to examine evidence based strategies for technology enhanced learning. Although we only created part of the courses, we still had a large amount of time to work towards the section that we did design. This is not the current situation that is occurring in schools and post-secondary institutions.

In contrast to online learning, emergency remote teaching is a strategy for academic continuity that takes a face-to-face or blended course and fast forwards it into a fully online remote format. This strategy doesn’t necessarily take into account pedagogy as it’s about survival and getting through the semester.

Some considerations that we had to take into account were to:

  • Manage expectations: communicating with students and other members of the teaching team to explain the changes.
  • Modify remaining assessments for a remote format: we needed to take into consideration possible equity challenges coming from access to software and hardware.
  • Select simple online tools: keeping in mind that students were also experiencing upheaval in all their courses and living situations, we were aware that it would be a lot to get students to learn a variety of new tools in a short amount of time. Sometimes we had to choose a simpler tool within our LMS’ constraints and compromise.

It was challenging to simply plug in pieces and run day by day. Everyday we would notice things we would change or resources that we would ideally leverage to support students. However, there just wasn’t time to locate such resources or such resources didn’t currently exist.

Given the uncertainty around the COVID-19 situation, the lessons learned from using emergency remote teaching will be helpful in planning for fully online iterations of our course in the event we need to continue with fully online distance teaching.

Info-visualization: Acid Base PhET Activity

Given the current COVID-19, I’ve decided to make this lesson fully online. I’ve highlighted some of logistical questions that came to mind based on the design and how an online high school class would look like.

This activity goes over acids and bases and attempts to use LfU with SKI supports. It also tries to model scientific inquiry through PEOE (predict, explain, observe, explain) and how scientists engage in critiques while targeting misconceptions.

Step 1: Motivation through PEOE

Predict the products and observations for the reaction when concentrated aqueous sulfuric acid is poured onto solid sodium chloride (Barke et al, 2009). Explain your thinking by using a molecular diagram. State any assumptions you make about the reaction conditions.

H2SO4 (aq) + NaCl (s) → ?

We aren’t expecting students to come up with a “perfect” answer here, but many might immediately treat this as a double displacement reaction. They might experience disequilibrium when they realize that the states of matter are not both aqueous. Some may conclude no reaction occurs when using their solubility table.

We don’t necessarily expect them to recognize how the sulfuric acid behaves with chloride ion and if they apply the Bronsted Lowry theory. Some of this may also depend on the specific reaction conditions.

Step 2: Knowledge construction by showing an answer, reflecting on the prediction, and trying to explain that answer

In one experiment, the reaction was shown to produce gaseous hydrogen chloride:

H2SO4 (aq) + NaCl (s) → HCl (g) + NaHSO4 (s)

In groups, compare your initial answers from Step 1 to Step 2:

  • Were you surprised by this answer?
  • Why is it that a reaction did occur in this case?

As a group, design a possible set up for the experiment that would be able to capture gaseous hydrogen chloride and how you would know that hydrogen chloride was produced.

  • Draw your lab set up (you can do this by hand and then upload a picture, or use online software like Chemix)
  • Create a molecular diagram to show what is occurring during the reaction
  • Justify your lab set up and explain how you would expect the reaction to proceed in the set up
  • How can you test the identity of the gas?

A question that came to mind for this section was how students would work together and what the domains of an online class would be. Do students go to each class as per their rotary timetable? How long is each class? In this current situation, it’s more likely that your high school classes are in the same timezone, so this is a bit easier to work within. Steps 1 and 2 could be synchronous for the whole class or asynchronous. There may also be synchronous drop-ins available through conferencing software (e.g., Google Meet, Microsoft Teams, Bb Collaborate, depending on what is available).

In terms of the chemistry, I want students explore how this answer may have been created and how that data was collected. Since this may have been an unexpected answer, I also want them to explore and explain what’s happening at the molecular level to see how students’ mental models are developing (Barke et al, 2009). It would be good for the teacher to check in with students to compare their predictions and new answers. It’s possible that students made assumptions about the reaction conditions that cause their answers to be different.

Step 3: Further knowledge construction and refinement through a synchronous class discussion

The synchronous class discussion would take place through video conferencing software where students get to view other groups’ designs and ideas. Before the session, groups should post their designs with a brief summary of their ideas in discussion forum.

In the live discussion, groups will explain their design and why they think it works. Peers will be able to provide feedback and ask questions.

Depending on your class, you might also record the class discussion and upload. You would need the class’ permission for this. The idea here is that students who may have been unable to attend the synchronous discussion will be able to watch later on. The sharing through the discussion forum also allows for asynchronous participation.

Through this discussion, we’re interested in seeing if groups suggest using an indicator (e.g., litmus, pH paper) on the gaseous hydrogen chloride. The teacher should also probe students into discussing acids and acid theory (Bronsted Lowry).

Step 4: Watch a video of a set up for the reaction

Some possible videos:

Depending on the video, the teacher might highlight the observations as needed. This should be connected to the previous discussion in Step 3. They should also correct any mistakes that are made in the video, if any.

It’s helpful for students to see a live demonstration and see what the observations were expected to be. This part could be synchronous or asynchronous.

The teacher could also show their own set up an experiment and comment on what the observations would be. A set up and the expected observations are included in Barke et al (2009). From the molecular diagrams that students drew, the teacher can pick one that was correct and/or explicitly model the expectations. This is important in getting students how to visualize and problem solve schematically as per the discipline (Edens & Potter, 2008). The teacher should explain what’s happening with the solvent interactions and how the Bronsted Lowry theory is applied to come up with the answer.

Step 5: Motivate by comparison gaseous hydrogen chloride and aqueous hydrochloric acid

In the set ups you created and in the examples we say, the pH was always taken on aqueous hydrochloric acid. In the cases where indicator was used over the stream of hydrogen chloride gas, the indicator paper was wet.

Why is this step done? Draw molecular diagrams for gaseous hydrogen chloride and aqueous hydrochloric acid.

This is the second LfU cycle. It lives within the larger anchored example, that served to motivate students with an unexpected and interesting reaction. It’s important for students to recognize that gaseous hydrogen chloride is made of molecules while an aqueous hydrochloric acid solution contains ions.

Step 6: Knowledge construction and refinement by exploring a PhET simulation

Using this acid base solution PhET simulation, examine the differences between:

  • acids vs. bases
  • strength
  • concentration
  • pH

Pick one solution of your choice. Note its concentration and pH. Change the view to graph. Create a concentration vs. species graph using a linear scale. What do you notice? Why does the PhET choose to use a logarithmic scale?

Come up with conclusions for each of the following:

  • Why do aqueous acids and bases conduct electricity?
  • If a strong acid and a weak acid have the same concentration, how do their pH and conductivity compare and why?
  • If a strong base and a weak base have the same concentration, how do their pH and conductivity compare and why?
  • If a strong acid and a strong base have the same concentration, how do their pH and conductivity compare and why?
  • Is a concentrated base the same as a strong base? Why or why not?
  • Draw molecular diagrams for hydrogen chloride gas, concentrated hydrochloric acid, and diluted hydrochloric acid. Include a caption for each image to highlight their features.
  • Solution X and Y both have similar conductivity and pH. If one solution is a dilute strong acid and the other is a concentrated weak acid, how would you distinguish between the two?

After a lot of internal conflict about this particular PhET, I started to see that it was intended to scaffold student learning and some of the visualization choices were done for simplicity. The simplicity creates productive constraints for students to work within and develop their mental models through interaction (Finkelstein et al, 2005; PhET Simulations, 2013). Being able to interact with each variable and see the effects also supports embodied learning (Niebert et al, 2012). By reading Burke et al’s (2009) recommendations on teaching acids and bases, it’s better for students to develop an understanding of acid base behaviour through a static model before they examine dynamic equilibrium. When the students work on the PhET, it might be helpful to explicitly tell them that they are looking at snapshots of what’s happening at the molecular level. Drawing attention to what’s not shown by the PhET (e.g., solvent interactions, dynamic equilibrium) would be helpful in starting the next LfU cycle.

References

Barke, H., Hazari, A., Yitbarek, S., & SpringerLink ebooks – Chemistry and Materials Science. (2009;2008;). Misconceptions in chemistry: Addressing perceptions in chemical educationLinks to an external site. (1. Aufl. ed.). Berlin: Springer. doi:10.1007/978-3-540-70989-3

Edens, K., & Potter, E. (2008). How students “unpack” the structure of a word problem: Graphic representations and problem solving. School Science and Mathematics, 108(5), 184-196.

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.

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

Info-Visualization: PhET and other Simulations

I shared resources for remote chemistry teaching, like visualizations and simulations from the Open Science Laboratory. Given the current COVID-19 situation, I selected these resources without really thinking about their pedagogical value. In many ways, it feels like survival mode. If I were teaching in high school right now, my thought process would be to:

  1. transition students to online learning as soon as possible, check in with students through the transition
  2. design for safety and accessibility; we don’t know where our students are logging in from or if at all
  3. design for asynchronous learning and supplement with optional synchronous sessions
  4. re-design and re-think assessments for a fully online experience

You may have noticed that my order links to pedagogy and technology before examining content specific pedagogy. My approach hints at trying to defer addressing the chemistry content. I don’t think chemistry can be taught fully online and that simulations are poor substitutions and replacements for actual experiences. However, given the circumstances, simulations and technology are the best alternative for what we might normally do as a real classroom experience. I will examine the cognitive affordances of PhET and a virtual lab, make recommendations about the use of these tools in an online design, and make suggestions about the role of teachers and students.

Cognitive Affordances of PhET and virtual labs

As I was examining a PhET simulation for my discussion post, I was thinking to myself:

I don’t know if I would use this. It’s technically not realistic and it can introduce more misconceptions.

The specific PhET simulation I was looking at was on acids and bases. I liked that the simulation visualized the species in aqueous solution and showed the equilibrium concentrations. However, I couldn’t help but critique that:

  • the simulation is inaccurate because the species are dynamic, students need to understand dynamic equilibrium
  • although there’s a graph to show the the equilibrium concentrations, it has a logarithmic scale. I understand that this is for space saving, but if students do not read the scale and examine the graph solely on visuals, they will misunderstand the equilibrium concentrations
  • solvent interactions are not shown

Going through the readings helped me recognize why these decisions were made and how they support the learning of acid and base solutions.

As Finkelstein et al (2005) explain, a simulation can be more effective than an actual lab because a simulation forces students into productive constraints. Given the nature and design of a simulation, students have a specific set of actions. Although this might not be realistic, the PhET video points out that this is aligned with cognitive science: we don’t want to cognitively overload the learner with information (PhET Simulations, 2013). Interestingly, it was denoted that having too much information at once makes learners become more passive; they begin to watch rather than interact (PhET Simulations, 2013). Hence the scaffolding provided from a simulation is in line with cognition and engages learners in constructing their learning based on the available variables. The simulations are not meant to be the only or primary example for students. Instead, they are an anchor point in the learning journey where students learn some part and when they develop an understanding, can proceed to the next layer of difficult.

This scaffolding and simplicity is in the acid base solution PhET. This particular simulation has an introduction and then a create your solution. In the introduction, learners begin to explore each of the key variables tied to type of species, strength, concentration, and pH. Explicitly learning the conventions for representation can help students unpack symbolic representations. Similar to how Edens & Potter (2008) examined visuals students created to unpack word problems, students may create graphical representations for acids and bases. Edens & Potter (2008) noted that schematic diagrams were more similar to what experts would create where the relevant data was mapped and expressed while pictorial diagrams were expressive and contained unnecessary information. From looking at the mental models for acids and bases in Barke et al (2009), this was similarly shown where students with lower understanding drew spheres without any semblance of what they represented in terms of the acid. In contrast, students with higher understanding used chemical formula (Barke et al, 2009).

In contrast to this PhET simulation, I didn’t find the Open Science Laboratory flame test lab as useful. I can understand that the simulation wanted students to understand the process of conducting a flame test, but it was a buggy set up. It could have been improved if there was more scaffolding, like an intro, to show the user the signals when a specific step was completed successfully. This could give better feedback and modelling about where the hottest part of the flame is and how to adjust the Bunsen burner. As is, the current flame test lab’s constraints are frustrating and not necessarily productive.

Recommendations for Classroom Use of PhET

Although PhET and other well designed simulations can be more effective than doing a physical lab, they cannot fully replace the learning of a real experience (Finkelstein et al, 2005). In terms of embodied learning, simulations should definitely be used in cases where the concepts cannot be experienced (Niebert et al, 2012). Like in the case of acids and bases, being able to change the parameters for key variables and observe what occurs at the molecular level is embodied.

Simulations can be used to help students visualize and interact with data. The conceptions they develop from this may be within the simulation’s constraints, but students should continue to engage in deeper learning once they have set up a foundational schema. In the acid and base PhET example, learning about the type of species, strength, concentration, and pH can address many misconceptions. There are purposeful constraints in the PhET design to force students to artificially examine these in a static environment. This manages the students’ cognitive load and facilitates their interaction with the variables. Once students have developed conceptions about these variables, dynamic equilibrium can be introduced.

Active Roles of the Teacher and Students

Based on the readings, I would suggest:

Teacher

  • select a simulation based on misconceptions students commonly have about a the topic
  • design a series of closed and open questions to stimulate student thinking
    • closed questions: test for understanding
    • open questions: encourage exploration, forming conclusions
  • create opportunities for follow up after using the simulation
    • include tasks that will have students visibly show their thinking, critique and correct misconceptions
  • create follow up activities to address some of the visual limitations in the simulation
    • highlight that scaffolding is being used
  • model the visual conventions and schematic representations for the concepts

Students

  • experiment with the simulation
    • try to come up with conclusions on the behaviours of each of the variables
  • participate in group discussions about the simulation and how it works
  • reflect upon past and current understanding and how/why it has changed

If I were to go back and teach high school chemistry, I would love to have students work on simulations in small groups. In line with a mixed LfU and T-GEM model, students would seek to solve a problem, and work on making conclusions through this simulation. The process of knowledge construction and refinement would be supported by group activities.

References

Barke, H., Hazari, A., Yitbarek, S., & SpringerLink ebooks – Chemistry and Materials Science. (2009;2008;). Misconceptions in chemistry: Addressing perceptions in chemical education (1. Aufl. ed.). Berlin: Springer. doi:10.1007/978-3-540-70989-3

Edens, K., & Potter, E. (2008). How students “unpack” the structure of a word problem: Graphic representations and problem solving. School Science and Mathematics, 108(5), 184-196.

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.

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

Knowledge Diffusion

How is knowledge relevant to math or science constructed? How is it possibly generated in these networked communities? Provide examples to illustrate your points.

Driver et al (1994) highlight the personal construction and social construction of learning science as a process that involves making sense of our everyday interactions with scientific phenomena and engaging in scientific discourse. These concepts parallel with Piagetian and Vygotskian theories. It is important for learners to engage in both personal and social construction because they should be able to engage in science in a variety of contexts. The commentary of Driver et al (1994) dismisses basic accretion and assimilation; their commentary parallels with Winn’s (2002) ideas of the umwelt. Essentially, as the umwelt (visualization of schema and connected schema) develops as students engage in cycles of equilibrium and disequilibrium. Through accretion, tuning, and accommodation, a more nuanced and vast umwelt develops and students will recognize and apply that some theories are more relevant in specific concepts. Depending on the scenario and context, students can switch between theories and recognize how they supplement each other.

For this module, I explored the Exploratorium and Virtual Field Trips. Both of these networked communities can be used to construct the learning of science. They allow students to develop their interests in greater depth and continue learning outside of the classroom. Depending on the resource used, students can join participatory cultures.

Exploratorium and similar open resources from museums

The Exploratorium’s online resources remind me of DIY activities. These could be starting points for deeper conversations. I really like how these activities are accessible and can encourage deeper learning. I did, however, find that the resources are more geared towards K-6, but I may also have this lens given the COVID-19 situation. When looking at resources from the Royal Ontario Museum, I couldn’t help but feel that things are better in the actual museum. I’ve always loved being able to go into the museum, wander through exhibits, play with the new tech experiences, and listen in to guided tours.

The online resources can bring the museum learning home. As Hsi (2008) mentions, museums and science centres are also supplementing visits with pre and post activities. I can see these online resources being used by students and their families to continue exploring topics. Although some resources appear to be more geared towards classroom teachers, they can be modified for family use. I really like how many of the activities can be project based so students are engaging in a variety of skills that are used by the scientific community (e.g., research, observation, communication) as well as other age-geared skills (e.g., fine motor, gross motor).

Virtual Field Trips

I watched the virtual field trip to Astra Zeneca. It was very similar to TV show episodes where you get an inside look into a workplace. The only main difference I noticed is that the host encouraged viewers to participate on Twitter with a specific hashtag.

Other modern equivalents of virtual field trips could include live streams, Instagram takeovers, and vlogs featuring things like a day in the life of _____ or an AMA (Ask Me Anything).

Virtual field trips allow users a selected glimpse into an environment they may not normally have access to. Since they are available on the internet, users can choose what they are interested in. In terms of what Driver et al (1994) mention about the engagement of scientific discourse, virtual field trips and conversations with the scientific community (research based and otherwise) humanizes and contextualizes what students have/will learn in the classroom. These virtual trips can also transcend what might normally be selected in the classroom curriculum.

References

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

Hsi, S. (2008). Information technologies for informal learning in museums and out-of-school settings. International handbook of information technology in primary and secondary education, 20(9), 891-899.

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

Role Play in Science

According to Resnick and Wilensky (1998), while role-playing activities have been commonly used in social studies classrooms, they have been infrequently used in science and mathematics classrooms. Speculate on why role playing activities may not be promoted in math and science and elaborate on your opinion on whether activities such as role playing should be promoted. Draw upon direct quotations from embodied learning theories and research in your response.

Why role play might not be used in science

Role play can be used to embody metaphors and analogies. Given that these have limitations where novices internalize similarities that are inaccurate or unintended, teachers would still have to explicitly explain the metaphor/analogy (Niebert et al , 2012). As well, experts might perceive the abstract concepts as concrete (e.g., chemicals are real) and just speak directly about them. As well, metaphors and analogies can fail. If the source is not embodied, the item is ambiguous due to differences in colloquial and academic use, or students are missing an experience, the metaphor can facilitate alternate conceptions (Niebert et al, 2012). The role plays that are used in a class may be constructed rather than embodied. Role plays have a script and are consequently constructed. However, the experience within a role play can be embodied depending on the script.

A teacher might spend a long time creating a great role play for their students. They construct the knowledge based on their experiences and map an abstract concept from their schema. However, when sharing this with students, the students may not understand or have difficulties because the role play is not embodied. It’s hard for the students to connect to the teacher’s knowledge construction and thus reject the teacher’s role play (Niebert et al, 2012). Due to the differences in the teacher’s and student’s knowledge landscapes, the meaning of the role play is not shared.

At the same time, role plays usually involve acting. If humans are representing particles, there are many human features that could be focussed upon rather than whatever the role play is attempting to highlight. I often find that the most common role play used is to representing bonding or forces of attraction. This is tricky because you can’t really model strength (the dating and love analogy might be used, but students might focus on the identity of their classmates instead) and the stochastic nature of the particles is not shown (students tend to stand stiffly).

The effort from constructing a role play and low return may make role plays undesirable in science classes. It might be “easier” if direct instruction or a simulation is used instead. However, this doesn’t necessarily mean that role plays should not be used at all. There are good use cases for role plays.

 

Example of a good role play

In my Advanced Inorganic Chemistry course there was one specific role play/metaphor that really stuck with me. My professor was talking about the metathesis mechanism. I can’t remember who the scientists were, but they were able to dance their paper to show how the mechanism worked:

  1. Two couples independently dance
  2. The two couples join together to form a box
  3. The group separates into two couples, different from the initial

This was a good role play because:

  • mechanism and dance both embody movement: movement of atomic connections vs. movement of people
  • dance focusses upon the dancer: using this schema, the focus is on how the dancers are interacting. Other information about them is dismissed
  • having users dance focusses upon the before, transition, and after formations
  • focussed analogy: we don’t examine the hand holding between dancers or the relationships between the dancers. Instead the pairing is connected to the linkage between atoms.

 

Potential of role play in science

I don’t think role plays should be dismissed as a tool in teaching science. Overall, I think if an experience can be embodied and experienced, this is how students should learn it. However, for abstract concepts, metaphors, analogies, and role plays can be useful. I would still prefer to use simulations if possible, but alternate expressions can be useful. I think they would be a good entry point to learning.

An example of a role play I might use is a human circuit to teach Grade 9 Science (electricity unit). This is a constructed role play but it does involve embodiment when the students start participating:

  • have two students represent a battery (one positive end, one negative end)
  • have students join the circuit by forming a closed loop
  • the student representing the negative end of the battery sends high tens (high fives with two hands) in the direction towards the student representing the positive end of the battery
  • high tens are passed from person to person
  • add in a student to represent a light bulb
  • if the high tens are successfully transferred from negative end to positive end, then the light bulb will light up
  • removing students from the loop and breaking it opens the circuit
  • can demonstrate parallel circuits by creating two branches from one student (the current is split, splitting is done by transferring just one high five into each of the branches)

I could also see myself having students create their own metaphors, analogies, and role plays to explain concepts. They would also be prompted to identify limitations and follow up assessments that should be used. Having students translate their learning into different forms can help them strengthen their schema.

References

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

Embodied Learning

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

Winn (2003) explains computational cognitive learning theory should not be dismissed over constructivism. Computational cognitive learning theory has continued to focus on cognition and learning. Current research links neural networks to mental representations, the computational analogy is useful to describe system behaviour, and the theory does not neglect biological adaptation. Winn proposes a framework for learning in e-environments; it emphasizes that our bodies externalize our brain activity by connecting cognition to the environment, we use our bodies to solve problems, and there is an interdependence between cognition and the environment. Importantly, Winn (2003) emphasizes that:

  • our cognition works within our physiological constraints: although technology can be helpful in expanding our perception, incomplete understandings or the medium used can introduce misconceptions. The symbolic system or distortion/simplification of a concept can lead to different understandings
  • embedded learning involves interaction with the learning landscape (umwelt): when students are learning, they are exploring what they already understand and discovering how these understandings connect/do not connect with new “views”. Challenge, curiousity, and fantasy are strategies to facilitate learning.
  • learning involves physical, cognitive, and social development; at least conceptual change at the short term level

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

Niebert et al (2012) comment on the role and quality of metaphors and analogies. Metaphors and analogies can help map a source schema to a target concept. Ideally, students should be able to develop embodiment with metaphors and analogies by experience. However, with abstract concepts, students must develop their imagination. Embodied metaphors are better than constructed metaphors because the latter requires students to re-construct their teacher’s metaphor. The differences here can lead to alternate conceptions and poor understanding. The students may completely reject the metaphor. In the examples given, metaphors can fail when the source schema is not embodied. Uncommon experiences, artificial experiences, lack of experience, and the differences between academic and colloquial language are all potential reasons why a metaphor may fail. In contrast, a good metaphor enables experience in the target domain, refers and reflects the embodied source.

I particularly liked the breaking a chocolate bar and cell division task. It was helpful in addressing the misconception that organisms grow through cell division only. After breaking the bar, students would realize that the bar isn’t any bigger and division makes smaller pieces. From this apparent discrepancy, students reach the conclusion that cell division also requires cell growth.

Adamo-Villani, N. & Wilbur, R. (2007). An immersive game for k-5 math and science. Proceedings of the 11th International Conference Information Visualization, 921-924. doi: 10.1109/IV.2007.23

The VR game in this article highlights how this medium supports embodied learning. Given the use of a headset that forces uses to see only what’s in the game and tools to pick up hand movements, user experience is set within the game. SMILE also included commercial game elements which helps with motivation and engagement. In the game, the learning that users experience is self paced, allows repetition, and helps players see and feel in concrete terms.

Questions for Further Discussion

  1. Have you used embodied learning in your class before? If yes, what did it look like? If no, do you see yourself using it in the future?
  2. Do you have any specific go-to metaphors when you’re teaching? If you could not use this metaphor, how would you teach the same concept?
  3. How do you envision VR being used in the future of the subject you teach? What are the challenges and opportunities with this?

TELE Synthesis: Connections to Engineering Design

In a colleague’s post, she mentioned how the TELEs do the same thing. I realized that this has strong parallels with engineering design! The function of the TELEs is the same, but the means of achieving the function are different.

Engineering Design Example

I think this analogy will help illuminate how achieving the same function through different means leads to a different experience.

In the case of the TELEs, we want our students to learn. In my example, we’ll start with a client statement and translate it into some engineering terms.

Client Statement: I want a bag to carry my stuff.

Client Need: Transport of mass

Function: Transport mass

Although the client wants a bag, the function is actually to transport mass. Here are some possible solutions:

  • a bag
  • a cart
  • a delivery service
  • a personal assistant
  • a sled led by dogs

Although some of these solutions appear nonsensical, they can all achieve the same function. However, the experience will be different for each one. What I haven’t considered in the design example is the broader considerations (e.g., objectives, constraints) and other aspects like the stakeholders and service environment. These considerations would impact the recommended solution.

 

Parallels to TELEs

In our case, the TELEs share the same function of learning. However, the means to achieve this are different. The locus of action (who is doing the constructing?) and how this is occurring (e.g., activity, concepts) differ.

The TELEs can be used in conjunction with each other. The selection and design of the TELEs will depend on the teacher, students, availability of technology, time, and other classroom requirements.

TELE Synthesis

A comparison of TELEs

I’ve had the TELEs jumbled in my mind for a while, but creating this chart has been helpful in identifying how they are unique.

TELE What it looks like Learning Theories Needs Addressed Key Affordances Things to be aware of
Anchored Instruction Jasper: video narratives with vignettes that contain relevant context to the scenario and a complex problem for students to solve. Students work on the problem with peers. They must consolidate multiple concepts and apply a variety of skills. Constructivism:

Multiple connections and links to schema for learning

Real context connects to sociocultural model

 Increase student motivation because the subject is contextualized in a real life case

Opportunities for complex problem solving.

 Peer-to-peer and collaboration

Video medium facilitates visualization and can be engaging

Video examples can be directly applicable to students or opportunities for learning new things that may not be immediately relevant to them.

 Video is expensive given the needs of the three levels of production

Teachers still need to be aware of the assessment and support for students

Language/context can be challenging for ELLs

Still need frequent and varied assessment

Potential for viral effect where students create their own video narratives and assessments

More modern alternatives to video include VR, AR, and MR.
SKI WISE: online modules that can support subject inquiry. Engage students through scaffolding and iteration. The scaffolding involves connecting to preconceptions, making predictions, and other resources. SKI is about chunking and sequencing the material. Cognitivism: scaffolding and chunking content

Constructivism: peer-to-peer and collaboration, continuous reflection

 High quality online learning objects

Open access

Re-mix and modification for individual teacher use

 Peer-to-peer and collaboration

Meant to replicate an inquiry process. This is modelled by reflection and re-visiting preconceptions

 Predicting pathways for learning and misconceptions: Look into literature and prior experiences

Need to revise for instructional based misconceptions

Be careful of the default affordances of the medium and how they may limit assessment and interactivity

Given the cognitivist influence, need to be aware of how students perceive fluency. Students prefer fluent learning experiences and may overestimate their learning (Deslauriers et al, 2019).

Would use teacher.desmos as the platform for SKI math
LfU Cycle of motivation, knowledge construction, knowledge refinement

Motivation: demand, curiosity

Knowledge construction: Observe, communicate

Knowledge refinement: Apply, reflect

 Constructivist

Skills are developed and concepts are learned based on the problem at hand

Strong parallels with Piaget’s concept of schema construction (assimilation, tuning, accretion, accommodation)

 Harmonizing process and content

A cycle of motivation and engagement

 Looks a lot like problem/project based learning where skills and auxilliary concepts are learned as part of the larger learning objectives Opportunities for differentiation

Need to remember that these are activity based and the activity can start the cycle of motivation
T-GEM Generate: form a hypothesis based on a large data set

Evaluate: put the hypothesis to the test, examine anomalies

Modify: revise hypothesis, examine new cases

 Constructivism

Appears to be more teacher-directed through the selection of activity

GEM also parallels with disequilibrium given that evaluation allows students to engage in accretion, tuning, and accommodation

 Addresses conceptual understanding and inquiry

Students work on explaining a theory and applying it rather than memorizing findings

 Models how the scientific community behaves through hypothesizing, analyzing data, discussing with peers, and iterating Generate and Evaluation phases are good places to use concept cartoons (for science) where students are engaged in disequilibrium and must address the strength of their schema’s connections

Students may incorrectly think that research and data collection is easy, given that simulations allow for rapid collection

Need students to appreciate the challenges of the past and the advancements to today

Technology and simulations need to be addressed, visualization and order can lead to misconceptions

 

Ranking from teacher-centred to student centred

This ranking is based on the nature of the TELEs, how technology is used in the examples we had, and is based on the default features:

  1. SKI
    Because the initial creation of a SKI module may arise from common misconceptions. The WISE modules were created to allow teachers to re-use/re-mix. Using the modules as is, is akin to using an interactive textbook with built in activities. SKI lends itself well to peer-to-peer collaboration, but the prediction of the learning path is determined by the creators. Face-to-face interactions and assessment can help teachers iterate upon existing SKI modules.SKI’s strategy for learning is scaffolding concepts. The locus of construction is at the teacher level.
  2. Anchored Instruction
    If we only look at the original Jasper series and the nature of video, this can be more teacher-centred. However the utility of peer-to-peer collaboration and rich assessment tasks can allow students opportunities to further explore. If the viral effect option with anchored instruction is used (i.e., students create their own anchored instruction series), there is a greater link to student oriented learning.
  3. T-GEM
    T-GEM strongly parallels scientific inquiry. Based on the Generate phase with the mass of data, T-GEM could be more teacher-centred depending on the data’s origins. The teacher may also be selecting the anomaly data for students to analyze. However, T-GEM is useful in getting students to iterate upon their theories and learn how to communicate their understanding using academic language. A challenge with inquiry in science at the high school level is that we are trying to move our students towards known conclusions. We want them to diverge, but really everything should converge to the same point. T-GEM has a nice approach to deal with these challenges because it iterates upon what is “known” by shaping it with feedback and unusual cases.T-GEM’s strategy for learning involves construction based on observation. The locus of construction is at the student level with teacher’s providing data.
  4. LfU
    Given the nature of the LfU cycle (motivation, knowledge construction, knowledge refinement) and engaging students through activity, LfU appears to be more student-centred. Given the prompt/activity, students learn related concepts and develop supporting skills to achieve their goals. Like the WISE modules, this can support lifelong learning.LfU’s strategy for learning involves motivation for activity. The locus of construction is at the student level.

In my own context, I can see how a mix of the TELEs would be used to support active learning in engineering design. However, as a non-engineer, I don’t have the appropriate TPACK to flesh out the details of this:

  • Pre-lecture tasks with SKI: Given that we have about 1000 students, it’s hard to provide one-on-one feedback. The classic pre-lecture task is to read a textbook, but I find that (at least in math, chemistry) textbooks aren’t written for novices and students don’t complete readings as we would expect them to. Given the nature of an active learning lecture, students would ideally apply their pre-lecture learning in lecture with facilitation from instructors and TAs. Using SKI for pre-lecture tasks would be helpful for students because they can complete activities and get feedback as they move along. These pre-lecture tasks would be housed within the LMS to track student progress.As well, students like fluent modules because they perceive that they are learning more in these cases (Deslauriers et al, 2019). The interspersing of assessment can be used to facilitate self assessment and metacognition.
  • LfU and Anchored Instruction: Due to the nature of engineering design, the course is more project based. The client’s problem serves as a real life scenario and it needs to be solved. This also contextualizes the learning that students do and the skills they need to develop to move towards a conceptual design. However, I’m not sure where the technology will come into play here. With the Jasper Series, the scenarios were selected for students and they were useful to view given that they weren’t necessarily places where students could go/experience. In our case with real clients or at least real client statements with fictitious clients, technology doesn’t do much to enhance the experience. I read about Nephrotex used as a serious game and virtual intership for engineering design, but I don’t have the engineering design knowledge to critique the use of technology here. It is a useful virtual internship but I don’t foresee our course being modified to include something like it for the time being.

What I like most about the SKI, LfU, and T-GEM frameworks is that they are strongly linked with Piaget’s theory of schema construction and modification (Yilmaz, 2011):

Overall, I’m seeing that regardless of the technology used the overall structure of learning needs to be framed within how people learn and assessment/activity. The educational technology used does not teach. The human interactions between teacher, student, and content is where the teaching and learning occurs.

References

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

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

T-GEM and Periodic Trends

I’ve been struggling with creating a T-GEM lesson because I’ve been hung up on the Generate phase. I can’t get over the need for a large data set to observe and generate a relationship! I’ve settled for periodic trends, but have some rough drafts for:

  • intermolecular forces and changes of state
  • real gas behaviour
  • different ways to fill/inflate a balloon
  • solubility (compound in a solvent vs. temperature)

Background: Periodic trends are a challenge for students.

When I marked my undergraduate chemistry students’ quizzes on periodic trends (e.g., defining the trend, explaining it, applying it) there were often challenges with explaining why the trend was as is and how to apply them in novel concepts. In particular, students memorize the trends to apply them to questions. When they are given elements to compare, they can easily use the trend without really understanding what’s happening. However, this misconception becomes clear when students are asked to rank information about isoelectronic species. What I’ve realized from teaching periodic trends to students is that they do not understand what these atoms look like nor do they recognize the importance of Coulombic attractions (re: charge and distance between charged particles).

Periodic Trends T-GEM Lesson

Generate

Using atomic radius data, the teacher will model how to explain the trend for atomic radius going down a periodic table:

Screen shot from periodic trends simulator. (American Association of Chemistry Teachers)

Students will identify that the trend going down the periodic table is that the atomic size increases. The Bohr Rutherford diagrams from H, Li, Na, and K will be drawn and connections to Coulomb’s law will be explained. It’s important for students to recognize the importance of:

  • protons attracting electrons
  • electrons repelling electrons
  • impact of distance between charged particles

With the Bohr Rutherford diagrams, the teacher must be very careful to explain that the circles where electrons are drawn represent energy levels, not orbits. The energy levels represent the distance from the nucleus to where the electrons can most likely be found; electrons in higher energy levels are further away from the nucleus.

Visually, students will see that the elements going down this group are increasing in size. This helps them follow along when the teacher models an explanation using Coulomb’s law.

Evaluate

To put their explanation skills to the test, students will predict the trends for atomic radius going left to right and ionic size as compared to the atom an ion was formed from. They are expected to explain this using Coulomb’s law (PhET simulation on Coulomb’s law.) and can compare their responses to this periodic trends simulator. The prediction and explanation for the atomic radius should be checked before students can move on to make predictions about ions.

Outside of the classic size ranking questions, they will arrange the following isoelectronic species in order of decreasing size: Na+, Mg2+, Ne, F–, O2-, N3-

Using Coulomb’s law, students should examine the number of protons and electrons to make their prediction.

Modify

As an extension and application of their understanding of atomic size, students will predict and explain the trends for ionization energy (going down the periodic table, going left to right). They will be provided with the definition of ionization energy (the energy required to remove 1 mol of the most loosely bound electron from 1 mol of an isolated neutral gaseous atom).

Students will examine the discrepancy in ionization energy in the oxygen family and explain why it exists. In this case, students will use their trend to make a prediction, and then compare their prediction to data (periodic trends simulator). Students will need to use the quantum mechanic model with an electron configuration diagram to figure this out. This will highlight that the Bohr model is useful in explaining the general trends, but another model is required for explaining discrepancies and developing a more nuanced understanding of the trends.

Another discrepancy to explain is the ionization energy of boron as compared to beryllium. Again, this requires a quantum mechanic model.

A note on technology and simulations

Although the periodic trends simulator. I’ve selected is useful, I don’t like some of the language it uses with respect to only being able to remove valence electrons to make an ion stable. Naked ions are NOT stable. Naked ions are not found in nature.

The simulator, along with instructional methods that talk about ionic stability, are missing the point that ions do not readily form in nature. We need to have a conversation about lattice stabilization energy. I remember this being a really confusing point in 2nd year inorganic chemistry. My professor commented that everyone thinks that sodium readily donates its valence electron to chlorine and chlorine willingly accepts to form chloride. This isn’t true as is. My professor specifically showed us the ionization energy of sodium and the electron affinity of chlorine and showed that it would be an endothermic reaction. This contradicts what we had all learned in high school! Then he commented that the missing picture was the lattice stabilization energy. Essentially, elements do not readily become ions!