Category Archives: e-folio

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Creating Inquiry and Exploration Throughout Our Lives

Piaget once said, “Our real problem is – what is the goal of education? Are we forming children who are only capable of learning what is already known? Or should we try to develop creative and innovative minds, capable of discovery from the preschool age on, throughout life?” (Davidson Films, time stamp: 0:41).

While I am nearing the end of the MET program, I must admit that at the beginning of the ETEC 533 course, I continued to carry a hindering bias toward the use of technology in the classroom. In addition to this, as a teacher originally trained for secondary English, I have found science and math to be the two courses that I struggle most with myself which, of course, has the potential to carry over into my teaching as well. ETEC 533 has been an incredibly valuable and meaningful course, allowing me to shift my perspective from digital technology as a distraction to digital technology as a supportive learning tool or environment, in relation to its ability to promote engagement, motivation, and inquiry-based learning, allow for embodied learning, and make learning visual for learners. Daniel Edelson (2001) addresses the fact that “educators have traditionally seen content and process as competing priorities” (p. 355) as opposed to being perceived as intersecting domains, along with knowledge, as introduced by Mishra and Koehler (2006). The more I reflect on my teaching experiences up to the start of this course, the more I realize that I have not put sincere consideration into whether or how I am integrating content and process as they relate to science and math, and I recognize that my use of digital technology has generally been a “competing priority” rather than being effectively incorporated into existing curriculum content to support student understanding and learning. My initial post in ETEC 533 clearly demonstrated the bias and uncertainty that guided my thinking and approach toward digital technology-based learning, “Based on the upbringing I had, I think I tend to shy away from using much digital technology in the classroom because of the amount of screen time I automatically assume students have at home” (Module A, Lesson 1.1, Auto E-ography) and in the video interviews lesson as I again admitted I “…have tended to shy away from using technology much in the past because I felt that students were receiving enough “screen time” (yes, I generalized and assumed screen time was screen time), and for many of the reasons that were given in the videos (i.e., time constraints, feeling ill-equipped, and so on)” (Module A, Lesson 2.2: Video Analysis – Case 5, Case 6 and Case 8). As I began ETEC 533, my initial questions revolved around effectively implementing technology into the classroom and how that implementation may impact other areas of student development, showing an uncertainty, hesitation, and lack of confidence in my own use of technology and understanding of how to integrate it effectively into my own practice.

As Xiang and Passmore (2015) discuss, the focus of science education has shifted “…from typical classroom practice that emphasizes the acquisition of content to a classroom in which students are active participants in making sense of the science they are learning” (p. 311). In the process of reflecting back on my learning experiences in ETEC 533, three concepts stood out above the rest: the concept of misconceptions that students both carry and develop, the concept that inquiry-based and embodied learning allow students to construct their own knowledge based on their personal observations and experiences, and the concept of virtual laboratories or simulated learning environments and their impact on learning in today’s classrooms. To support these concepts, I now appreciate that digital technology must be incorporated in order to allow students to develop the skills needed to truly be 21st century learners. William Winn (2003) points out, “successful students are anything but passive” (p. 13) and in order to design a curriculum for my current and future students that is engaging and motivating, I have realized through this course that I must focus on how to design inquiry-based, student-centred, and collaborative learning environments, supported through the use of digital technology.

In his Conceptual Challenges post, Lawrence Liang (2017) wrote, “Misconceptions are rife in student minds because misconceptions are common in educator minds. Misconceptions are, as Confrey wrote, ideas and meanings about their world that they formulate to explain how or why things occur (Confrey, 1990)…What results may be a blend of the ideas, both accurate and inaccurate, as students attempt to come to terms with a topic.” For me, the two most significant points learned, in terms of misconceptions, are that educators often assume that students have learned and understood certain concepts and, even more importantly, that “misconceptions are common in educator minds.” The concept of misconceptions is one that I realize I have unintentionally addressed in my classroom through some of the activities I do with my students; however, I have not specifically targeted misconceptions in the past, and it would be more accurate to say that I have perhaps “stumbled” upon them up to this point, especially in the science classroom. The topic of student misconceptions has had a significant impact on my own learning and perceptions from the very beginning of ETEC 533 when it was originally introduced and I began to identify personal learning gaps, recognizing that if my students do not share their misconceptions with me, I may never realize they have misconceptions or preconceived notions about concepts we are learning. In “A Private Universe”, teacher, Marlene LaBossiere, draws attention to the fact that, “You just assume that they know certain things…I just assumed that they had the basic ideas, and they don’t” (“A Private Universe,” 1987, time stamp: 8:55).” As I continued to learn more about misconceptions, I began to understand “that children approach science with ideas and interpretations despite not having received instruction,” depending on their prior knowledge and experiences (with reference to Driver, Guesne and Tiberghien, 1985) and “…students enter the classroom with their own understandings of the world…often at odds with the scientifically accepted view of the world” (Henriques, 2000, p. 1) (Module A, Lesson 1.2: Children, Science, and Conceptual Challenges). As ETEC 533 progressed, I realized the potential that digital technology provided for significantly more interactive, engaging, and motivating learning environments for students in today’s classrooms, which could, in turn, help students understand and challenge their misconceptions, especially through the interactive approach afforded by simulated and virtual learning environments.

It was during Module B and Module C that my interest in and understanding of the importance of inquiry-based learning really began to develop, expanding to incorporate students’ construction of knowledge and embodied learning, as opposed to a transfer of knowledge from teacher to student. In his post, “TELE Synthesis”, Darren Low (2017) commented, “First and foremost, all of the theories are rooted in the theory of constructivism – the notion that learning occurs through an active process, not a passive one. Students construct their own learning through specific, active and repeated experience and activity, not by simply being told the information (Fosnot, 2013). It is upon reflection of these novel concepts that prior understandings and ideas are consolidated into a single, new understanding. The role of the educator is primarily as a guide, assisting students along their path through the exploration of these exercise and activities and not as a conveyer of information, dispelling information through lecture and notes. Through these process, students are able to acquire a deeper understanding, typically, through inquiry.” To encourage an inquiry-based, constructivist approach to learning, students must be given the opportunity to explore concepts more independently and through their own observations and experiences, rather than having knowledge simply transferred to them through lectures and textbooks. Information and data must be delivered in a variety of ways, allowing students to engage with materials and concepts using multiple senses and a range of learning experiences. As Hasselbring et al. (2006) highlight, students “need to acquire the knowledge and skills that will enable them to figure out math-related problems that they encounter daily at home and in future work situations” (no page number available). Project-based learning, in turn, “allows for increased emphasis to be put on student-centred learning, rather than on the teacher simply imparting knowledge through memorization and recitation that the learner is then often unable to access when needed (Edelson, 2001)” (Lesson 3 (LfU): Including and Motivating Students of Today). Adding to this, the incorporation of processes like GEM (or T-GEM) allow for skill development in a cyclical pattern around the learning process of generating, evaluating, and modifying ideas (Khan, 2007 & 2010). It was during the exploration of the GEM/T-GEM model that I recognized a significant weakness within my own teaching practice that could be improved through the integration of GEM into the design of my own classroom lessons and projects. I realized that I often struggle with what I perceive as time constraints and because of this, I often do not allow students adequate time to complete an exploratory process like GEM. By incorporating GEM into my own lessons, students will be given the opportunity to generate ideas, both independently and collaboratively with their peers, form their own hypotheses, evaluate both new and existing data, then re-evaluate hypotheses and ideas generated based on what they have learned. T-GEM, along with the TELEs explored throughout ETEC 533, will allow me to design an inquiry-based and collaborative learning environment for current and future students.

In the diverse classrooms of today, one significant concern for me has been how to create an inclusive and accessible environment for all learners. In exploring technology-enhanced and virtual or simulated learning environments, the extent to which digital technology promotes the inclusion of all students in diverse classrooms, collaboration between peers, an engaged exploration and evaluation of data, and the individual and shared generation of ideas, has become increasingly clear. Bodzin et al. (2014) emphasize the importance of including “design features in instructional materials so that low-level readers and low-ability students can understand scientific concepts and processes in addition to learners whose cognitive abilities are at or above the intended grade level” (pp. 13-14). Similarly, Radinsky et al. (2006) address differentiated assessment, allowing educators to assess students’ knowledge and comprehension from a variety of perspectives, and for students to show their learning in a variety of ways. In addition to this, processes like Anchored Instruction, WISE, LfU, and using virtual or simulated learning environments, provide students with an opportunity to engage in interactive learning activities that connect their learning to reality outside the classroom, bringing classroom learning to life and making it authentic and applicable for learners. In her post, “Learning in Artificial Environments,” Anne Winch acknowledges, “Winn notes that cognition is embodied in physical activity, that is embedded in the learning environment, and that learning is the result of the adaptation of the learner to the environment and the environment to the learner (Winn, 2002)… A student’s engagement and identity as a learner is shaped by his or her collaborative participation in communities and groups, as well as the practices and beliefs of these communities (Dunleavy, Dede, & Mitchell)” (Wincherella, 2017). As I came to understand in Module B, “Students learn through a process of constructing new knowledge through personal experience and communication, rather than having knowledge transferred to them; through goal-directed learning initiated by the learner; through the creation, elaboration and accessibility (storage) of knowledge; and through the understanding of and ability to use factual knowledge and then transform that knowledge into procedural knowledge (Edelson, 2001; Radinsky et al., 2006)” (Lesson 3 (LfU): Including and Motivating Students of Today).

With my Framing Issues paper, I began to examine “The Effect of Virtual Laboratories on Student Achievement and Success in Chemistry.” From here, I was able to extend my questioning to achievement and success in science and math more generally. When I began ETEC 533, I felt that a traditional hands-on laboratory experience was most successful and educationally sound in terms of student understanding, interaction with materials, and learning; however, it became clear relatively quickly that this assumption was incorrect. While traditional laboratories provide students with important and interactive learning opportunities, the knowledge I have gained through ETEC 533 has demonstrated that virtual laboratories and other simulated learning environments promote student engagement and motivation, are often more economically feasible, allow for the repetition of experiments to build comprehension and confidence, allow for experiments that may be considered too dangerous to be attempted otherwise, and decrease the time taken to prepare for and clean up after traditional laboratory work (Tatli & Ayas, 2013; Tüysüz, 2010; Martínez-Jiménez, Pontes-Pedrajas, Polo, & Climent-Bellido, 2003; Robinson, n.d.). As Tyler Kolpin (2017) commented in response to an energy forms and transfer lesson I created using a PhET interactive simulation (titled “Energy Forms and Changes”), “This kind of visualization is so valuable due to the high cost of actually going through the motions of creating this experiment.” Kolpin’s point prompted me to reflect on the fact that this experiment, among many others offered through PhET and other simulation platforms, allows students at even a relatively young age, to engage in interactive laboratories and simulation work that they would not otherwise have been exposed to due to the cost of materials, time and equipment/space constraints, and so on. By providing students with the opportunity to engage in simulated or virtual laboratory environments, students are again engaged and motivated as they interact within an authentic and accessible learning environment that allows students to transfer and apply their knowledge to the “real” world. As I discovered in Module C, Lesson 3, “Finkelstein, Perkins, Adams, Kohl, & Podolefsky (2005) found that when the right learning environment was created, simulations could be equally effective, if not more effective, learning tools than traditional laboratory equipment “both in developing student facility with real equipment and at fostering student conceptual understanding” (p. 1-2)” (Module C, Lesson 3 [Information Visualization]: Energy Forms and Transfer in Science 4).

As I complete my ETEC 533 journey, I am no longer left with a lingering question of whether digital technology could help support learners in my classroom, but am instead optimistic about the integration of many TELEs, simulations, and virtual learning environments into my curriculum content and process. Rather than treating technology as a separate entity, I understand the need to actually incorporate it into everyday learning for students, and my lingering questions revolve now around how to integrate students’ own devices to support a digital-technology enhanced environment in the classroom. Finally, I have a solid understanding of, and research to support, the incredible importance of project-based learning within today’s classrooms. To allow for inquiry, collaboration, and construction of knowledge, students must be allowed to explore and generate their own ideas, which means stepping away from the board and the textbook, and presenting students with time and freedom to discover learning for themselves.

References:

Bodzin, A. M., Anastasio, D., & Kulo, V. (2014). Designing Google Earth activities for learning earth and environmental science. In MaKinster, Trautmann, & Barnett (Eds.) Teaching science and investigating environmental issues with geospatial technology (pp. 213-232). Dordrecht, Netherlands: Springer. Retrieved from http://www.ei.lehigh.edu/eli/research/Bodzin_GE.pdf

Davidson Films, Inc. (uploaded 2010). Piaget’s developmental theory: an overview [online video]. Retrieved from: https://m.youtube.com/watch?v=QX6JxLwMJeQ

Driver, R., Guesne, E., & Tiberghien, A. (1985). Children’s ideas and the learning of science. Children’s Ideas in Science (pp. 1-9). Milton Keynes [Buckinghamshire]; Philadelphia: Open University Press.

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.

Energy forms and changes. (n.d.). Phet Interactive Simulations, University of Colorado. Retrieved from https://phet.colorado.edu/en/simulation/legacy/energy-forms-and-changes

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.

Harvard-Smithsonian Center for Astrophysics (Producer). (1987). A Private Universe [online video]. Retrieved 6 January, 2017, from: http://learner.org/vod/vod_window.html?pid=9

Hasselbring, T. S., Lott, A. C., & Zydney, J. M. (2006). Technology-supported math instruction for students with disabilities: Two decades of research and development. Washington, DC: CITEd, Center for Implementing Technology in Education (www.cited.org). Retrieved from: http://www.ldonline.org/article/6291/

Henriques, L. (2000, April). Children’s misconceptions about weather: A review of the literature. Paper presented at the annual meeting of the National Association of Research in Science Teaching, New Orleans, LA. Retrieved 7 January, 2017, from: http://web.csulb.edu/~lhenriqu/NARST2000.htm

Khan, S. (2010). New pedagogies for teaching with computer simulations. Journal of Science Education and Technology, 20(3), 215-232.

Khan, S. (2007). Model-based inquiries in chemistry. Science Education, 91(6), 877-890

Kolpin, T. (2017, April 5). Comment to “Energy forms and transfer in science 4” (Sikkes). Retrieved 6 April, 2017, from http://blogs.ubc.ca/stem2017/2017/03/31/energy-forms-and-transfer-in-science-4/#comments

Liang, L. (2017, Jan. 11). Is it worth constructing incorrect knowledge? [STEM: Conceptual Challenges]. Retrieved 6 April, 2017, from http://blogs.ubc.ca/stem2017/2017/01/11/is-it-worth-constructing-incorrect-knowledge/

Low, D. (2017, Mar. 8). Tele Synthesis [STEM: Synthesis Forum]. Retrieved 6 April, 2017, from http://blogs.ubc.ca/stem2017/2017/03/08/tele-synthesis/

Martínez-Jiménez, P., Pontes-Pedrajas, A., Polo, J. and Climent-Bellido, M.S. (2003). Learning in chemistry with virtual laboratories. Journal of Chemical Education, 80(3), 346-352.

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

Radinsky, J., Sacay, R., Singer, M., Oliva, S., Allende-Pellot, F., & Liceaga, I. (2006, April). Emerging conceptual understandings in GIS investigations. Paper about forms of assessment presented at the American Educational Research Association Conference, San Francisco, CA. Retrieved from https://www.researchgate.net/profile/Joshua_Radinsky/publication/242390299_Emerging_conceptual_understandings_in_GIS_investigations/links/54eb39670cf27a6de11763ab.pdf

Robinson, J. (n.d.). Virtual laboratories as a teaching environment: A tangible solution or a passing novelty? Southampton University. Retrieved January 25, 2017, from: http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=528C202CA72A6A6252236F58981824B1?doi=10.1.1.11.6522&rep=rep1&type=pdf

Tatli, Z. and Ayas, A. (2013). Effect of a virtual chemistry laboratory on students’ achievement. Educational Technology & Society, 16(1), 159-170.

Tüysüz, C. (2010). The effect of the virtual laboratory on students’ achievement and attitude in chemistry. International Online Journal of Educational Sciences, 2(1), 37-53.

Wincherella. (2017, Mar. 16). Learning in artificial environments [STEM: Embodied Learning]. Retrieved 6 April, 2017, from http://blogs.ubc.ca/stem2017/2017/03/16/learning-in-artificial-environments/

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 1-28. Retrieved from: http://isites.harvard.edu/fs/docs/icb.topic1028641.files/Winn2003.pdf

Xiang, L., & Passmore, C. (2015). A framework for model-based inquiry through agent-based programming. Journal of Science Education and Technology, 24(2-3), 311-329.

Redefining Mathematics and Science – One Educator’s e-folio

Working through the e-folio process has been quite insightful. I actually ended up laughing, with a bit of head scratching, at some of my earlier writings from the beginning of the course. 🙂

Here is the link for anyone interested, as well as an alternate way for Samia to access the blog.

Cheers, everyone! It’s been a pleasure!

 

http://blogs.ubc.ca/jessicaholderetec533/

 

 

Model-based Instruction and Learning – A Better Understanding through NetLogo

Throughout this MET533 course, the instructor, Dr. Samia Khan, has diligently commented on student blog postings by affirming student thinking, offering further guidance, and posing questions for deeper inquiry. Several of Dr. Khan’s comments to my own posts were intentionally written, I believe, to spur me on to more thoroughly consider model-based learning and its purposes. Using prior knowledge and previous perceptions I attempted to ponder the use of models within instruction and teaching, yet it was not until the T-GEM lesson during Module B that I began to see more clearly the direction which Dr. Khan was gently pointing.

For interest’s sake, samples from Dr. Khan’s comment prompts on model-based instruction and learning are posted below:

From “Conceptualizing Misconceptions”:

Your careful comparison of the role of visual representations in fostering partial or incorrect conceptions leads one to wonder in what ways can children’s drawings contribute to understanding in math and science and our assessment of what they know?


From “Plate Tectonics: Reshaping the Ground Below Us”

I wanted to focus in on the process of modeling for this post, which lends itself nicely to the area of plate tectonics. Gobert et al. in their paper that students can engage in model-based reasoning with models, be they dynamic, runnable visual models in WISE or ones created from physical materials such as that of the plates or the Earth. For example, one of the first activities is for students to draw a model of how mountains are formed and then explain within WISE what happens to each of the layers when a mountain is formed. Students then critique peer models using prompts in WISE such as, what do you think should be added to this model that would make it better for someone who does not know geology. Peers then revised their models by examining and considering these recommendations.

The Geology Book is currently being used to support the construction of models, and I was wondering in what ways some of these model construction, reconsideration processes be fostered in some of the activities that you already have (eg. with WISE) or with hands on-materials?


From “Staying Afloat: Sink and Float Density T-GEM”

In the modification phase, asking students to design a pictorial representation (model) of the data is one way to begin to inspect their conceptual understanding. it will be interesting to see how students represent heaver objects in these pictorial models.


By investigating varied information visualizations, specifically NetLogo, further understanding of model-based instruction and learning has developed. NetLogo contains similar features to some of the instructional frameworks studied in Module B i.e. WISE/ SKI and T-GEM. These similarities offer rich inquiry opportunities for learners and include: being overseen by experts, allowing for teacher collaboration and authoring, offering exploration of micro and macro phenomena, and student modification of models to observe patterns and anomalies. Other affordances evident in NetLogo are similar to PhET as described in the study conducted by Finkelstein, Adams, Keller, Kohl, Perkins, Podolefsky and Reid (2005). Key characteristics of inquiry simulations include an emphasis on discovery rather than verification and allow for the exploration of microscopic behaviors or patterns that are not physically observable in real-life scenarios. As described by Finkelstein et al. (2005), “[a] variety of visual cues in … computer simulations make concepts visible that are otherwise invisible to students” (p.6). Students are able to make meaning of observable global activity by viewing localized patterns. Resnick and Wilensky (1998) refer to this type of modelling as an exploratory model “start[ing] with rules for the individual parts of a system, and … observ[ing] the group-wide patterns that arise from the interactions” (p. 162). Another feature described by Finkelstein et al. (2005) is the limited nature of simulations when each simulation is designed around a focused topic. This aspect of limitation is evident in NetLogo as specific models are available across a breadth of domains, including sciences {biology, physics, chemistry, social,} mathematics, computer science, and art. Interestingly, rather than inhibiting learning, the limitations tend to result in enhancing learning by minimizing distractions caused by excessive choices. Finkelstein et al. (2005) describe this enhanced productivity in the following way:

[B]ecause the system under investigation is constrained in particular ways, students are able to make progress they cannot in an unconstrained environment… Simulations provide the instructor considerably more freedom in designing and applying constraints to ensure that students’ messing about leads to productive learning. Constraints are also valuable as students mimic real scientists and mathematicians by isolating individual variables. This isolation of variables supports student understanding “by focusing attention to relevant details… [that can be] effectively applied to physical “real world” applications. (p.7)

As a distance learning teacher working with elementary students within a range of grade levels, I have concluded that NetLogo simulations are a better fit for upper level elementary learning (i.e. grades 4-7). Browsing through the model library does takes time, yet even within my own limited exploration several models were found that could effectively be incorporated into student elementary programs i.e. Biology/Autumn (Wilensky, 2005), Biology/Sunflower (Wilensky, 2003) and Mathematics/Color Fractions (Wilensky, 2005). This latter model is quite interesting as students decide upon and view a connection between fractions, decimals and visual box patterns. This model is simple enough for a grade 4 student to modify when beginning to learn how to correlate fractions and decimals through curriculum. Each NetLogo model contains a “Model Info” section which is an invaluable feature providing teachers and students with an explanation of the model, what to pay attention to when modifying, ideas for modification, and extension ideas. This “Model Info” is an asset for successful understanding and implementation.

In conclusion, NetLogo is one example of a simulation exemplifying theoretical research through a model-based learning experience. Students are provided the opportunity to explore and discover patterns determined by their choice of modifications and scaffolding is provided within the “Model Info” section to help direct students through guided inquiry. It is necessary for both teachers and students to understand the need for invested time to become familiar with the limited variables, as this is essential in building connections. Viewing phenomena in a new and meaningful way is highly probable through NetLogo and this affordance is something, that I believe, Dr. Khan’s guided inquiry was helping lead me to see.

 


Finkelstein, N.D., Perkins, K.K., Adams, W., Kohl, P., Podolefsky, N., & Reid, S. (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.

Holder, J. (January 12, 2017). Conceptualizing misconceptions [Web log message]. Retrieved from https://blogs.ubc.ca/stem2017/2017/01/12/conceptualizing-misconceptions/

Holder J. (February 20, 2017). Plate tectonics: Reshaping the ground below us [Web log message]. Retrieved from https://blogs.ubc.ca/stem2017/2017/02/20/plate-tectonics-reshaping-the-ground-below-us/

Holder, J. (March 3, 2017). Staying afloat: Sink and float density t-gem [Web log message]. Retrieved from https://blogs.ubc.ca/stem2017/2017/03/03/staying-afloat-sink-and-float-density-t-gem/

Resnick, M. & Wilensky, U. (1998). Diving into complexity: Developing probabilistic decentralized thinking through role-playing activities, Journal of the Learning Sciences7(2), 153-172. DOI: 10.1207/s15327809jls0702_1

Wilensky, U. (2005). NetLogo Autumn model. http://ccl.northwestern.edu/netlogo/models/Autumn. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Wilensky, U. (2005). NetLogo Color Fractions model. http://ccl.northwestern.edu/netlogo/models/ColorFractions. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Wilensky, U. (2003). NetLogo Sunflower model. http://ccl.northwestern.edu/netlogo/models/Sunflower. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.