Final Analysis

I came into this course with pretty straightforward goals and open-mindedness about where the course would take me and what aspects of technology for teaching STEM would be explored. As a base, I was eager to learn the following research-backed aspects of teaching STEM:

new tech tools,
best practices for designing lessons and courses,
strategies to motivate and engage learners, and
theories for increasing retention of information.

The readings and discussions in this class leaned heavily into these goals and provided new ways of teaching and designing STEM classes. This final analysis will illustrate my learning progression this term and highlight five themes that stood out to me as I reviewed my discussion posts and responses and the readings I chose for each lesson. I will carry these themes forward in my job to create more effective STEM learning experiences.

Theme 1: Engagement Strategies

One theme throughout my e-folio is the notion of engagement. Science and math can be dull and challenging to many students; as such, their attention spans can be quite short. As I noted in Anchored Instruction Symposium, if it takes more than 5 minutes to solve a problem, students get discouraged and give up (Cognition and Technology Group at Vanderbilt,1992), but evidently, technology can play a significant role in keeping students interested and offloading cognitive strain so that students can learn more effectively.

Technology to Reduce Cognitive Strain

I had a revelation about technology as a support tool; it should not be seen as the enemy or a cheat to students but rather a handy tool. In response to a peer, I commented on the use of calculators as a tool rather than a hindrance: “Hasselbring, Lott, & Zydney (2005) found that … calculators were a really helpful and simple tech tool that offered students support to reach their ZPD (Zone of Proximal Development, Vygotsky) independently and actually improved students’ ability to retain information long term. As such, one of their conclusions was that calculators and other tech tools help students offset some of the cognitive load to the computer, so they can focus on the deeper problem at hand.“ My conclusion is that as teachers, we are afraid that if we let students have resources, it means they aren’t learning, but in truth, the research shows we are stunting them if we withhold. We should lean into technology to help students overcome their fundamental misunderstandings, so they can become engaged in the deeper, more interesting problems, which will hopefully, inadvertently, help them make sense of the fundamentals. It’s a bit backward, but the more involved they are in their learning, the more effort they will put into it, and technology, like calculators, can support that engagement. As Paula_Huddy indicated, she gives students the answers so they can focus on developing the proper process. This evolution of thinking and teaching so that students can dive into more profound concepts is a valuable lesson.

Engaging Students with Embodiment

Another aspect of engagement I think is important to note here is the idea of embodiment, which was a new concept to me this term. To me, learning with movements and dynamic physical actions sounded like something out of a drama class rather than a science or math class, but I kept my mind open to the concept. Two conclusions from Novak et al. (2014) surprised me:

Embodiment can help students learn abstract concepts.
Gestures can relieve the cognitive burden on students and help them better verbalize their thoughts.

I appreciated NickRobitaille’s comment in the Embodiment discussion that helped me connect the dots to physical movement as a different way for students to communicate. Incorporating embodiment strategies into lessons is a method that opens up a new dimension of communication that many students are likely appreciative of, particularly those who sometimes struggle to articulate their thoughts. What I take away from this is that students are not meant to sit still; they are intended to move, and they learn and remember best when they can connect the mind with the body.

Theme 2: The Value of Identifying Learner’s Initial Misconceptions and Scaffolding Learning

The reading and learning theories presented in this course deepened my understanding of the value of prior learning assessments and how to make them meaningful to students and teachers. I’ve always encouraged prior learning assessments to help students show what they already know, but I’ve strengthened my understanding of how to build on that information and how technology can support it. Allow me to illustrate that progression. In week 2’s discussion, I wrote that educators should understand students’ baseline knowledge to progressively build upon it while just staying slightly ahead of a learner’s current level of understanding (e.g., keeping them in Vygotsky’s Zone of Proximal Development). I also suggested that technology can help students with less prior knowledge reach the mid-line more quickly. In week 5’s discussion, I started to consider how I might uncover learner misconceptions when planning a course’s design to account for proper flow, speed of progression, and necessary places to add extra instruction and support. Then in weeks 6-10, I refined my ideas for prior learning assessment activities and scaffolding them to encourage more critical thinking among students. A big ‘aha’ here was that we don’t need to reinvent the wheel – we can take that prior learning assessment and build upon it with the activities in a lesson, so students can see their progression of understanding, as we saw with the GIS system in week 8, where students use the same map but continually build upon it throughout the lesson.

One question I found myself returning to was how to address the skills gap among varying levels of knowledge in a class, as is commonly the case in science and math courses. When students lack foundational skills, it can be challenging to build on them, which is where scaffolding, supported by tech, becomes critical. I found the tenets of the SKI framework insightful, particularly the idea of making thinking accessible and visible and connecting that again with Vygotsky’s Zone of Proximal Development. I think it’s essential to find that spot where learning is just slightly above a learner’s current level and allow the teacher and technology to support them in their knowledge growth. Technology enables students to identify the exact point where they went wrong and gives them immediate feedback to correct their understanding (Confrey, 1990; Hattie & Timperly, 2007) and also gives teachers data on student progress and areas of weakness so that they can better support on an individual level (Linn et al. 2003).

I was surprised when putting together my summary of TELEs in week ten that all four models we looked at in Module B were based on the concepts of scaffolding and constructivism. This either evidences that the best model in a STEM classroom is one of scaffolding, that other models haven’t been explored, or that scaffolding is the best model in all classrooms, especially STEM; I lean towards the latter at this point, and I will take that conclusion forward into my future course designs.

Theme 3: Encouraging Students to Think and Learn Like a Scientist

As a student, the scientific method always seemed like a daunting and rigid sequence of tasks, but it should be used as a primary pedagogy in STEM classes. The models we’ve learned in this course (WISE, LfU, GEM) make use of the scientific method more casually and authentically, whereby they have the essential elements – hypothesizing, gathering data, testing, and communicating results – but don’t treat the lesson as a formal six-step process for the students; it becomes much more fluid and adaptable, much like how real scientists conduct their work. This illustration reinforces the need for refinement in the experiment phase, so students learn that it’s ok to make mistakes and be wrong, which are skills we need to encourage more in STEM courses. Students shouldn’t be discouraged or demoralized when they hit a roadblock or their experiment doesn’t work; instead, they need to understand that almost nothing is done right the first time and learn the confidence to troubleshoot and try again.

Communication and Collaboration

Perhaps the most valuable lesson I have learned this term is that communication and collaboration play a much grander role in STEM classrooms than I ever assumed, which fits right in with creating an authentic scientific experience. People interact and learn from each other constantly in the real world, so we need to mirror this in the classroom. Learners gain significantly more knowledge when they are given the opportunity to talk through ideas and learn from others (Linn et al., 2003), and this becomes truer when tech tools and simulations are involved (Peddle et al., 2019; Mattila et al., 2020; Grover et al., 2015). Already in my recommendations to clients, I am encouraging more group work and opportunities for peer interactions in their courses.

To that, everyone thinks differently. I’ve always felt this, but I don’t think it’s

consistently been encouraged in classrooms. However, many readings in this course brought this to light. Collaboration and group work can help emphasize different perspectives and evolve a learner’s understanding. In the Auto e-ography forum, I replied to a post indicating that one person’s takeaway from a game may not be the same as someone else’s. Winn’s concept of the umwelt (Winn, 2003) and the tenet of helping students learn from each other in the SKI framework (Linn et al., 2003) exemplify this.

To bring this conclusion full circle, I frequently checked on my previous discussion posts to see if anyone had added to the conversation because I wanted to continually gain different perspectives from my peers and refine my thinking as I continued to build my understanding throughout the course. It was a very meta realization.

Theme 4: Learner Autonomy, Agency, and Presence

I have evolved my understanding of learner autonomy and giving students a choice. One aspect of autonomy where my thoughts have matured is a pedagogical model where the teacher is a facilitator, not a lecturer, which elicits more curiosity among learners. Moving away from a traditional model, the teacher is now there to support and provide guidance while the student controls and actively participates in their learning. I think it’s hard for teachers to initially shift to this model as it puts a lot of trust in the students to stay on task, but increased student presence (i.e., active participation in their learning) was shown to induce curiosity amongst learners and get them more involved and motivated in their learning (Winn, 2003). As learners immerse themselves in their learning, staying on task won’t be an issue. Furthermore, when students are given meaningful tasks to work on and are encouraged to identify and solve problems, they are given agency to explore different approaches. This teaches curiosity and fosters the development of lifelong learners (Linn et al., 2003), which is essential for increasing learner autonomy.

In the past, when I thought about giving students a choice, it was primarily a choice of discussion or assignment topics or a vague suggestion of using video instead of writing an assessment. I quite liked the suggestion from the Video Case Studies in week three and Bencoulombe’s response in the Conceptual Challenges Forum for the use of stations, some of which are tech-based, in a classroom as another opportunity for student autonomy and choice in how they learn and demonstrate knowledge. When designing for online, I think the idea of stations becomes even easier to facilitate; there is a vast selection of technology and tools available on the internet that can be incorporated into a course to provide ample exploration opportunities for students, for which they can choose what they explore and how long they spend on each. While it takes more time to set up, the result is an immensely personalized learning experience that learners will be more engaged with and find more meaningful. With that though, as designers, we need to consider the number of options we provide learners and find the balance between meaningful and overwhelming. We want them to feel like they have time to explore everything, should they choose, or they can sink their teeth into one or two that capture their attention.

Theme 5: Authentic Learning

Having advocated for authentic learning over the last couple of years, it was interesting to see my conclusions throughout the discussions. Technology-supported authentic learning in STEM can:

engage students in the learning process (Viewing the Cases forum; Synthesis Forum),
increase transferability of skills (Anchored Instruction Symposium), and
deepen understanding of concepts (LfU Forum).

Teachers must bring the applications of the real world into the classroom to better connect concepts and make them memorable for students, but it’s the affordances of tech tools that make authentic learning much easier to incorporate.

Transferable Skills and Just-In-Time Learning

My biggest takeaway in this vein is that, in STEM, it’s not necessarily the individual learning objectives that equate to real-world learning, but rather teaching students problem solving, reasoning, logic, and critical thinking skills. With all the tools available nowadays, a lot can be done to teach these skills in engaging ways. Students need to know that not everything they learn will ever be used, but these concepts help them build critical thinking and problem solving, precisely what the Jasper Video Series demonstrated. As I concluded in the Anchored Instruction Symposium, “Jasper series is based on authentic scenarios which can be applied to multiple subjects, so they encourage critical thinking and transferable skills, which is important for elementary students just as it is for undergraduate and graduate studies.”

The other important aspect to highlight here is just-in-time (JIT) learning. This means that the teacher does not have to spend significant time lecturing about a particular concept upfront when it is virtually meaningless to students. Instead, suppose we use a more holistic, problem-based learning approach, as demonstrated in the Jasper Series, and allow the need for a particular formula to arise during the lesson. In that case, the teacher can take the opportunity to teach it when it is more relevant and memorable to students. This represents how students learn in the real world – we wait until we are presented with a problem, then we work to solve it, finding the relevant information and methods as we go. This JIT approach would work well in science and math lessons.

TPCK

Another critical conclusion is that tech is not a replacement; it is an enhancement and must be used purposefully to support pedagogy and content (Mishra & Koehler, 2006). I think this quote from Mishra and Koehler (2006) sums it up: “[O]ffer learners authentic and engaging ill-structured problems that reflect the complexity of the real world …Learners have to actively engage in practices of inquiry, research, and design in collaborative groups…to design tangible, meaningful artifacts as end products of the learning process.” (p. 1035). Particularly when designing STEM lessons, purposeful tech can enhance the pedagogy, so students can more effectively increase their understanding of content, particularly abstract concepts (Khan, 2010).

Conclusion

While there were many themes related to technology and teaching STEM courses presented in this course, I focused on those that will help me create the most effective learning experiences. When designing science and math courses, I strive for authentic learning that is engaging and purposeful, so this analysis helped me reflect on what critical design components are required to meet this goal.

Surprisingly throughout this analysis, I frequently refer to Linn et al. (2003) article, WISE Design for Knowledge Integration. This is interesting because I didn’t regard it as highly influential during the term, but it seems to have several overlapping concepts with many of the themes I’ve highlighted. I think it is imperative because the SKI model affords inquiry-based scaffolding without being too heavily structured, which makes it easier for the teacher or designer to adapt to more lessons and provides effective pedagogy.

When I look back on all the tools and theories we covered this term, I can’t help but notice a significant gap – what does evaluation look like in STEM classrooms? We covered much about learning from the student’s perspective and pedagogy from the teacher’s perspective, but we didn’t explore assessment in depth. How best should a teacher assess? From the readings, I can surmise that we need to go beyond basic written multiple-choice tests because those are not authentic, but what does authentic assessment look like for STEM? How is learning equitably evaluated? What tools for evaluation are most effective? I want to explore these questions more to round out my design practices.

On another note, AR and VR are valuable subjects that can lend themselves to enhancing STEM learning, particularly when it comes to engagement, embodiment, and authentic learning, but the solutions are not scalable at this point, so I chose to focus my attention on other themes that are more applicable to me today. As technology evolves and the tools to build individual AR and VR simulations, like Chemland or GIS, become available to average teachers and designers, this will become an increasingly important subject to follow.

A lot of learning took place this term that drastically evolved my thinking on how science and math classes should adapt to create learning experiences that meet modern students’ needs.

References

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