Author Archives: alicewong

Finding Alternatives – Usage of Information Visualizers

Indeed, visualizers are immediate and efficient tools to consolidate understanding. However, visualizers should not simply be regarded as tools for constructing rudimentary conceptual relationships. Rather, information visualizers should also be used to observe alternative thinking models.

More than meets the eye

Scholars strived to find hypothesis to explain why there were no differences between different sized groupings that used information visualizers (Stephens & Clement, 2015). Much of the recent scholarly discussion moved away from investigating how visualizers to construct understanding to optimizing the use of visualizers. More specifically, scholars are investigating about the ways in which specific features of these digital tools benefit users. These “objects to think with” have distinct features that enable users to correct misconception and provide possible alternative thinking models. Features like instant feedback, hassle free play and holistic perspectives make information visualizers appropriate tools that can support users’ search for new thinking models.

 

Instant Feed Back  

One of the most salient features of information visualizers is the interactivity of the digital components. Most visualizers have customized variables that provide instant feedback without requiring users to click additional buttons. Instead of the rigid change and consequence relationship, the seamless manipulation shows progressive changes that are almost undetected in real-time. Quite possibly, this real-time feature helps users develop a deeper understanding of the relationship between variables. More importantly, by observing the gradual change, users can make new and alternative assumptions. This feature exposes the users to more data and results. This feature is found in all three examples of information visualizers (i.e. Netlog, Geometer and Phet).

 

Hassle free explorative play & learning scaffolds

Undoubtedly, real-time tracking variables are most definitely a prized feature, however, hassle free explorative play and appropriate scaffolds also allows students to take advantage of visualizers. Physical laboratory experiences are often coupled with lessons to consolidate learning. During labs with physical objects, rather than spending time to support content learning, teaching assistants use their time to assuage administrative needs such as physically preparing materials (Srinivasan, Perez, Palmer, Brooks, Wilson & Fowler, 2006). Given the hassle free set up, it releases students to engage in explorative play. This is significant because “[t]his play can lead to the organization of students’ knowledge and its alignment with scientific models.” (Finkelstein, Perkins, Adams, Kohl, & Podolefsky, 2005, p.5) In the grouping study mentioned previously, scholars found that teaching strategies also allow students to attain positive learning gains (Stephens & Clement, 2015). Likewise, it is important for educators to scaffold learning with visualizers. Currently, some tools has explorative suggestions, hints and redirections messages that help students explore alternatives. In NetLogo, there are many variables to manipulative. However, it may be more helpful if the extensions are clearer. Moreover, even though there are teaching guidelines, pHet lessons may require more specific directions to extend learner’s thinking process.

 

Complex System & Holistic Perspective

While visualizers are often praised for their ability to show micro steps and slow down the process, it also provides a holistic look. Often, the whole system is visible in information visualizers. This fully supports Jacobsen & Wilinsky’s (2006) idea that sometimes learners have to understand concepts that are embedded within a larger complex system. This top-down perspective also alludes to other variables that may influences. Hence, if the current model fails to explain results, students can easily observe other variables to develop alternatives. In pHet lessons, users are usually able to see the whole system that learners are manipulating.

 

Implications

Although it may be rather early to make the assumption that visualizers should be use solely for deepening understanding. Yet, it may be time for educators to modify their paradigms about the usage of visualizers for surface level learning. Here are some suggestions:

  • Educators should consider using information visualizers that have explorative suggestions.
  • Educators should couple specific learning scaffolds to help students extend their thinking.
  • Researchers should continue to investigate variables that influence the usage of visualizers to modify thinking models.
  • Digital tool designers should consider adding more explicit directions to explore alternative thinking models.

 

Reference

Jacobsen, M. & Wilinsky, U. (2006). Complex systems in education. Scientific and educational importance and implications for the learning sciences. Journal of the Learning Sciences, 15(1), 11-34. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1207/s15327809jls1501_4

Srinivasan, S., Perez, L. C., Palmer,R., Brooks,D., Wilson,K., & Fowler. D. (2006). Reality versus simulation. Journal of Science Education and Technology, 15 (2), 137-141. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1007/s10956-006-9007-5

Stephens, A. & Clement, J. (2015). Use of physics simulations in whole class and small group settings: Comparative case studies. Computers & Education, 86, 137-156. Available in Course Readings.

Stieff, M., & Wilensky, U. (2003). Connected chemistry – Incorporating interactive simulations into the chemistry classroom. Journal of Science Education and Technology, 12(3), 285-302. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1207/s15327809jls1501_4

Knowledge Diffusion & Communicative Advantages

  • How can learning be distributed and accelerated with access to digital resources and specialized tools and what are several implications of learning of math and science just in time and on demand?

The ubiquitous potential of learning technologies has direct personal and indirect societal educational benefits. Digital resources and specialized tools allow for the development of a positive feedback loop for learning. In particular, the tools increase communication channels, hence boosting the frequency of communication and thus allowing for wider access and enhancing exposure for all problem solvers and inquisitors. If given the premise that accelerated learning is about being part of a learning community, indeed, technological develops helped distribute and accelerate learning by communicative advantages.

 

Enhanced Access – Communication Avenues

At a individual level, as new technological tools are developed, it also increases the number of ways in which information can be communicated. This makes it easier for learners to attain required information for learning. Consider the idea of a world library. The intention behind this project is to connect books with people (Kelly, 2006). There are multiple communicative platforms for users to choose from. Students now have access to multiple platforms to explore their paradigms and conceptual relationships. For example, with the development of hyperlinks, users are redirected to similar resources. More over the enhanced communicative methods helps differentiate and personalize learning. For example, video and or auditory are often successful solutions for students with low literacy skill levels and or special needs. After all, “[m]ental computation has limitations which can be overcome through written computation.” (Carraher, Carraher & Schliemann, 1985, p.28) It is also easier for students to access and explore graphical representations of more complex concepts. Beyond access to information, students can actively translate their understanding to their community in multiple ways. Together, these developments allows for learning outside the traditional classroom. As ideas are more widely spread, it increases the likelihood of exposing personal misconceptions and conceptual change. For example, on demand knowledge helps fill in learning gaps and confronts students with possibly opposing information.

 

Increase intensity – Communicative Frequency

Beyond directly enhancing personal access and expression, digital technology also indirectly allows for more opportunities to exchange ideas. Since digital tools connect information and solutions with people, more options allows for more frequent and effortless contacts. Instead of waiting for students to get to school to obtain an answer, users can send messages via asynchronous methods such as email or synchronous choices via collaborative tools like live chats.

Moreover, since learners have more platform flexibility, this communicative freedom increases the amount of opportunities for an educational discussion. Students then have more chances to actively engage with the learning. Educators can take advantage of this to promote learning by providing timely feedback. Moreover, with the support of technological tools, students will be quicker to identify and correct their misconceptions.

 

Participation – Building a community

Most importantly, how would these two communicative benefits accelerate and build the learning community? Some scholars believe that knowledge becomes productive when it can be found. Specifically, Kelly (2006), mentioned earlier in this post, suggests the value derives from a piece of work increases when shared. Unfortunately, “[o]nly 15% of all books are in the public domain” (Kelly, 2006). The writer claims that contributors can take advantage of this technology by ensuring their work is searchable in the networked libraries. This development then eases the process of participating in a knowledge-based community. Driver, Asoko, Leach, Scott & Mortimer (1994) believes that with knowledge, learners actively take part in accelerating the knowledge in a scientific community. Taken the notion that knowledge is productive and useful, this view envisions students as productive and contributing members of the greater learning community. Consider anchored instructions or WISE, where students contribute by submitting their response to the learning community.

 

Hence, the development of digital technology directly enhances personal and social communicative means, allowing for

 

Reference

Carraher, T. N., Carraher, D. W., & Schliemann, A. D. (1985). Mathematics in the streets and in schools. British journal of developmental psychology, 3(1), 21-29. Available in Course Readings

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

Kelly, K. (2006, May 14). Scan the book. New York times.

 

 

 

Lightbot – Implications of Embodiment in Coding

“Learning is considered to arise from the reciprocal interaction between external, embodied, activity and internal, cerebral, activity, the whole being embedded in the environment in which it occurs.” (Winn, 2003, p.22)

The premise of embodiment relies on constructivist ideas of learning. Students learn to use their body to process and demonstrate conceptual understanding. The research about embodiment also resonates with other notable theories such as the social-communicative learning. Here, the context in which the learning occurs serves as a decisive factor for concept attainment.

Let’s explore the ways in which the use of embodiment principals will support the learning of logic and coding in the application Lightbot.

Coding: Lightbot

  • Makes learning concepts concrete, tangible and accessible

Some theorists believe that “the body is a public resource for thinking, learning, and joint activity” (Stevens, 2012, p.338). More specifically, like artificial manipulatives, the body acts as a medium of processing information. Stevens quotes William (2012) and claims that “the “bodily basis of the conceptual system we use to think mathematically” (p. 217).” (Stevens, 2012, p.342) Adding muscle memory tags can also enhance information retrieval rate.

In the coding application Lightbot, users are asked to solve puzzles of command to direct a robot to light a light bulb in a specific space. Using hand gestures will also users to indicate the specific direction in which the robot will move hence supporting the problem solving process.

  • Embodiment allows for and utilizes learning from the first person perspective

The idea of embodiment expect learners to internalize and re-represent heard or seen concepts. They are commanding their body parts to materialize thoughts and communicate understanding. Moreover, it is possible that learners are mobilizing mirror neurons (i.e. to copy the agent and or the object) to re-represent and internalize explanation. This implies that the use of body parts to enable first hand experience hence increasing opportunities for direct experience. Kim, Roth & Thom (2011) alludes to the idea re-represent with body and that it is similar to utilizing slow motion to take a closer look at concepts and to reduce misconceptions.

In the case of solving puzzles in Lightbot, learners have to impersonate the robot to problem solve from their avatar’s point of view. Thus, the only way to solve the puzzle is to follow through imaging oneself as the robot.

  • Providing social learning opportunities to make concepts more explicit

In one study, it was found that almost all gestures were used for social interactions. More specifically, “[t]he body participates in abstracting the ideas unfolded in the interaction imaginatively and spontaneously.”(Kim, Roth & Thom, 2011, p.224) Naturally, body parts are accessible tools for social negotiation. When young learners lack the vocabulary to share ideas, body parts serve as convenient tools to express meaning. Embodiment theorists then claim that verbalizing alone is insufficient to create learning pathways.

With more challenging Lightbot puzzles, students will have to work together to help how they solve it. Here, the use of gestures and other body parts to share expertises.

Wonderings

How can the use of embodiment reduce misconceptions?

How can VR and AR technology support learning in coding?

How does immersive technology support the concept of embodiment?

 

References

Kim, M., Roth, W. M., & Thom, J. (2011). Children’s gestures and the embodied knowledge of geometry. International Journal of Science and Mathematics Education, 9(1), 207-238. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1007/s10763-010-9240-5

Stevens, R. (2012). The missing bodies of mathematical thinking and learning have been found. Journal of the Learning Sciences, 21(2), 337-346. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1080/10508406.2011.614326

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114. Full-text document retrieved on January 17, 2004, from: http://www.hitl.washington.edu/people/tfurness/courses/inde543/READINGS-03/WINN/winnpaper2.pdf

Emergent Themes in TELEs

TELEs can be in various forms. The following table compares and contrasts their underlying assumptions.

Anchored Instructions in Jasper SKI & WISE LFU & My World T-GEM & Chemland
Focus /Uniqueness Instructions are given via video Making learning – accessible, visible social, foster life-long learning. Motivate learning; Students learn to use/analyze a data set. Students have to evaluate and modify their thinking models.
Knowledge is… Socially constructed via problem solving Constructed as students complete an inquiry Constructed via learning to use tools to examine a set of data and making inferences Constructed via making and testing assumptions
Technology is utilized… As a method of delivering instructions. (i.e.video primary) As a platform for student to embark on their inquiry project (i.e. document thoughts) As information source to draw inferences between variables

(i.e. big data)

 As tools to explore and construct thinking models and to check the validity of the model
Learning happens… Through developing a solution to the outlined problem Through developing an inquiry Through cycles of inquiry Through cycles of inquiry
The teachers’ role is… To provide a pre-described case and background knowledge and to scaffold inquiry To select and provide a electronic platform that has prescribed inquiry To help scaffold learning during personal inquiries To help scaffold learning during personal inquiries
The students’ role is… To solve a problem and develop a solution To embark on a prescribed inquiry on an online platform To assess information and identify trends in online data base To use digital tools to generate relationships between concepts and
How are misconceptions assuaged? Through applying skills and solving a defined problem Through observing expert opinions and following an inquiry Understanding is refined through reflection and application Students actively search for models to explain new information; existing models of thinking is modified and refined

 

This chart is reflective of the fact that each model has a defined premise about learning and digital tools. It is apparent that these theories as based on the assumption that having access to and co-existing with technology does not equate to learning. These theorists also believe that students need to actively monitor their thoughts to assess and reflect upon conceptual relationships. Critical thinking skills and quality engagement opportunities with concepts are essential and effective ways to construction meaningful understanding about variables. Given this analysis, it is evident that the anchored instruction pedagogical model resembles more closely with WISE and LFU and T-GEM shares more similarities. Three clear themes emerged from this analysis.

Student Agency

Quite visibly, anchored instructions and WISE models provide a prescribed inquiry pathway for its learners. In comparison, educators do not prepare the inquiry map and direction in the LFU and T-GEM pedagogy. Students have full agency to inquire about the content and decide on the direction of their learning. The anchored instruction and WISE model place a stronger emphasis on educators to direct inquiry. For example, educators provide information for initial case and inquiry. They also direct how the model can be refined. This can materialize as extra sections in WISE and additional information and scenarios in the anchored instructions videos.

In the latter two models, learning relies on student’s audacity to inquiry upon their assumptions. More specifically, students choose their inquiry questions after inspecting a data set or defining their problem. Students have to actively find evidence to support and confirm their thoughts. Hence, students have a full control of the content and inquiry path. Students also decide on how their models are refined and or modified.

 

Attitudes towards digital tools

Collectively, all of these TELEs are consistent with Jonassen’s (1998) idea about students using digital tools to alleviate cognitive load. Clearly, these models share the idea that students should take advantages of digital tools in order to inquire like scientists. However, the reasons for and the intensity of usage vary. Specifically, anchored instructions and WISE uses technological tools as a platform for inquiry. Compared to LFU & T-GEM, students in the anchored instructions and WISE learning model require constant and direct access to first-hand information. Here, digital means are mere vessels to store information. More specifically, students are to collect and assess their own data.

Without access to technology, it is impossible to employ anchored instructions and the WISE model. However, it is still possible to use offline material to employ the LFU and  GEM teaching model. Both WISE and anchored instructions utilize technology as an all-encompassing framework. However, LFU and GEM perceive technology as reference information storage tool where getting pockets of access may be sufficient.

Knowledge & Knowledge Refinement

Anchored instructions and LFU designers believe that sources of knowledge come from data sets and are accessible via digital means. Another way to frame this is that anchored instructions and WISE believers assume that knowledge comes from pre-designed experiments and selected social sources like experts. In contrast, students in the LFU and TGEM learning design have to create, build or collect personal evidence to defend their thinking models. Moreover, anchored instructions and WISE are more concerned with forming inferences. While LFU and TGEM designers also believe in forming inferences, they extend the idea this idea and emphasize the need to confirm or reject inferences.

These inferences are further refined. While reflection and critical analysis is use in all TELEs, yet, these models diverge on how and in what ways reflection is used. For example, in anchored design and WISE, reflecting happens while applying their knowledge. In LFU and TGEM, reflecting equates to evaluating the accuracy of their inferences. In other words, anchored instructions and WISE are building knowledge in a bottom-up manner. Hence, students are slowly building a refined thinking model. For LFU & TGEM, knowledge refinement is a top-down process. This means that students first infer the overarching conceptual relationships then modify and refine their thinking models.

Clearly, TELEs are built upon certain premises and assumptions about what knowledge is and how it is constructed. These perceptions influence the way in which digital tools are engaged. Nonetheless, it is the educators’ choice to employ teaching models that is consistent with their beliefs. However, it is quite possible that one teacher may utilize multiple TELEs for different subjects. Additional research may help identify the interactions between components of TELEs, content and students’ learning dispositions.

Reference

Jonassen, D.H., Carr, C. and Yueh, H.P. (1998) Computers as mind tools for engaging learners in critical thinking. TechTrends, 43, 24-32. http://dx.doi.org/10.1007/BF02818172

 

Scaffolding a (T)-GEM: Magnetic Fields and Current

“ The inquiry processes evident in GEM included students’ finding patterns in information, generating hypothetical relationships involving three or more variables, evaluating the empirical consistency of information, coordinating theoretical models with information, and making predictions.” (Khan, 2007, p.898)

Khan (2007) purposes a learning model for students to gain first hand experience defining and refining relationships between variables. Although T-GEM provides a explicit framework, however, something seems to be lacking. When Khan (2007) inspected the teacher’s verbal response, it became clear that specific teaching strategies are required. Instead of identifying skills as teaching methods, scaffolds are a more fitting variable. Upon closer inspection, the T-GEM pedagogical model works harmoniously with problem solving scaffold foci outlined by Kim & Hannafin (2011). In combination, the teacher’s scaffolding role is made more specific and applicable.

Here is a design that provides suggestions about scaffolding prompts according to each step of the GEM cycle. Students will investigate the relationship between the strength of the induced field, current voltage, relative distance to the current, the direction of field and Earth’s magnetic field.

Students inquire about:

  • Strength of electromagnetic field changes relative to the current (i.e. current voltage and position of compass)
  • Strength of electromagnetic fields in relationship with flipped currents (i.e. current voltage & electromagnetic field)
  • Strength of induced fields (Investigate the relationship between strength of the induced field, current voltage, relative distance to the current, direction of field and Earth’s magnetic field.

Using the simulation from the Gizmos (i.e. Magnetic Induction), students can manipulate the voltage of the current and the position of the compass. Students will observe how the needle moves relative to voltage and location to the probe. The needle is parallel to the magnetic field lines.

G – Generate Hypothesis

Problem Solving Phrase: Exploration

Scaffold foci: problemization & internalization

In the case of T-GEM, students are asked to consult a data set, identify patterns and generate a hypothesis. This is consistent with the exploration phase of problem solving. Khan (2007) emphasizes that students are asked to propose a defining statement about the relationship between concepts. Kim & Hannafin (2011) supports that during exploration, students benefit from embedding scaffolds that ask students to identify anomalies and conflicting evidence.

Using the Gizmos (i.e. Magnetic Induction), students can place compasses around a wire. The simulation allows students to explore and change the voltage and the location of the compass. More specifically, students can observe the changes of a compass and the corresponding values when placed in multiple locations around the wire, when current is set at:

  • 0 amps
  • 60 amps
  • -60 amps

Students are asked to make an explanatory statement about the relationship between the direction of the needle, the voltage and the direction of the compasses.

 

E – Evaluate

Problem Solving Phase: Reconstruction

Scaffold foci: Internalization, generalization

In this phase, students’ hypothesis is taken to a test. More specifically, proposed models are confronted with new information. Khan (2007) expresses that this is a key phase where original models are challenged. Inferred conceptual relationships are refined in order to be applicable to new contexts. Here, it is important to support students with “[s]caffolds [that] help guide students to challenge their thinking, consider alternative evidence, and evaluate alternate solutions.” (Kim & Hannafin, 2011, p.410) The scaffolds that can support this will help reduce and or alter misconceptions. “[S]tudents generate and revise potential solutions and explanations as they encounter confirmatory or contradictory evidence.” (Kim & Hannafin, 2011, p.410)

To refine thinking model, students switch to magnetic field view, observe the following:

What happens the the compasses under these conditions…

  • Same current: far vs. close to the current
  • Same location: strong vs. weak current

This time, students click on the view show magnetic sensor. Record the change in values.

M – Modify

Problem Solving Phase: Reflection & Negotiation & Presentation & Communication

Scaffold foci: collaboration, feedback

This phase shares many similarities with the discussion part of a study. In light of the observations, students make inferences and informed predictions about the ways in which the variables interact. Students are to reflect upon their experience and offer an explanation about observations. Often through in-depth reflection, it may initiate new insights and investigations. However, it can be difficult to connect evidence to theory. Therefore, students may benefit from collaborating with peers. Thus, scaffolding foci for the presentation and communication problem-solving phase assist in helping students solicit feedback and inspire new ideas. Moreover, content scaffolds will help make relationships more explicit. Content prompts can also help students refine their models. When discussing about electromagnetic fields, understanding the science behind the induce fields from a running current may support learning (e.g. Magnetic field and wire; Faraday’s Law etc.). Since these new models requires confirmation, this inspires a new cycle of GEM.

 

 

Reference

Khan, S. (2007). Model-Based Inquiries in Chemistry. Science Education, 91(6), 877-905. doi:10.1002/sce.20226

Khan, S. (2011). New Pedagogies on Teaching Science with Computer Simulations. Journal Of Science Education & Technology, 20(3), 215-232. doi:10.1007/s10956-010-9247-2

Kim, M. C., & Hannafin, M. J. (2011). Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice. Computers & Education, 56(2), 403-417.

Gizmos – Magnetic Induction https://www.explorelearning.com/index.cfm?method=cResource.dspDetail&ResourceID=611

Mag Lab – Magnetic field around a wire 2

https://nationalmaglab.org/education/magnet-academy/watch-play/interactive/magnetic-field-around-a-wire-ii

Phet – Faraday’s Law – https://phet.colorado.edu/sims/html/faradays-law/latest/faradays-law_en.html

 

Learning For Use – Earthquakes

  • Imagine how LfU principles might be applied to a topic you teach. Now switch out the My World technology. What other domain specific (and non-domain specific) software might help you achieve these principles while teaching this topic? By domain-specific, we mean software designed for STEM education, and by non-domain specific, we mean software or other forms of technology that could be used generally in multiple domains (eg. Wikis). Other GIS software can be selected for the switch.

Learning for Use (LFU) is a constructive teaching pedagogy that emphasize on constructing and refining relationships between abstract concepts. Distinct from other learning approaches, LFU includes ways in which people can support social emotional states when learning (i.e. motivation). This learning model strives to decrease misconceptions by refining conceptual relationships. Another definitive feature of LFU is that learners must apply their knowledge. More specifically, “learning how to use conceptual knowledge must be part of the learning process, if the knowledge is to be useful.” (Edelson, 2001, p.357) Uniquely, LFU theorists suggests that although this model is relatively linear, it also synergistic in a sense that as students work through their inquiries, they are more motivated to learn. Their reflection also promotes opportunities to expose learning gaps, hence, motivating them to learn.

 

Design

Instead of My World, this design employs a collection of educational tools to support understanding of earthquake’s epicenter and magnitude. Designed for students grade 6 or higher, learners work through labs to understand how to use data from seismograms to determine the location of the epicenter of an earthquake.

Motivating learners

Edelson (2001) supports that students have to become aware of their own learning gaps and should be motivated fill in these knowledge gaps. Here, it activates students’ prior knowledge of earthquakes and exposes misconceptions.

Students are given seismograms to observe and consider. Students design a map as a response to the following scenario: If an earthquake magnitude of 5.0 happened in downtown Vancouver, locate safe areas for emergency responders build an earthquake refuge. Using the earthquake simulator, compare student created maps and actual map. Students redraw new locations for possible areas of safe refuge.

Knowledge Construction

Edelson (2001) claims that an important part of this stage is to allow students to investigate and observe information by using simulations to further decipher the relationships between variables.

In pairs, watch through Virtual Reality Earthquake Simulation (i.e. Pai-away) to develop basic knowledge about earthquakes. Learners also work through a Gizmos lab (i.e. Earthquake 1) to supplement their understanding about seismographs. Students work through the activities guideline to learn strategies to study about the relationship between incoming signals, time difference and distance. Engage in whole class discussion about factors that contributes to an earthquake and signs about the distance from the epicenter.

Knowledge Refinement

Reflection and application are two key features of this part of the learning (Edelson, 2001). Students have to critically analyze information and use observations to support their claim about the relationship between concepts.

Students work through an additional Gizmos lab (i.e. Earthquake 2) to learn about using seismographs to determine the epicenter. Students screenshot their findings and publically share strategies of finding the epicenter of the earthquake.

Knowledge Application

In order to make conceptual relationships between variables more memorable, students has to demonstrate that they can apply their knowledge.

In a small group design data for a hypothetic earthquake and provide graphs and corresponding map to show the epicenter of an earthquake and locations of possible earthquake refuges.

LFU & Big Data

Interestingly, there is a connection between LFU and big data. In essence, My World and other GIS software are databases with inquiry tools. Notably in WISE and LFU, students are asked to analyze information available in a database. They conduct experiments to collect and analyze data. Research in big data inquiring about drug discovery and databases suggests that these tools facilitates collaboration and allows users to use one simple interface to generate hypotheses and possible novel solutions (Ekins, Clark, Swamidass, Litterman & Williams, 2014). Hence, using inquiry methods, these learning spaces allow students to collaboratively learn about a topic.

The Future of LFU

Using Jonassen, Carr & Yueh’s (1998) idea of technology as tools to share cognitive load, imagine the future of LFU. With applications like Science Journal, with a phone’s sensors, users are able to easily collect local data for experiments. This provides hopeful outlook on independent experimentation. Students are no longer reliant on access to collaborative databases. Rather, they can easily and systematically peruse scientific inquiry by using technological tools to generate data, document and annotate findings.

Discussion Directions

Consider the use of Pai-Away VR simulation in this design. How can VR support LFU?

LFU is designed to help learners to become a data analyst. Agree or disagree. Why?

Reference

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.

Ekins, S., Clark, A. M., Swamidass, S. J., Litterman, N., & Williams, A. J. (2014). Bigger data, collaborative tools and the future of predictive drug discovery. Journal of computer-aided molecular design, 28(10), 997-1008.

Gizmos Labs https://www.explorelearning.com/  

Jonassen, D.H., Carr, C. and Yueh, H.P. (1998) Computers as mind tools for engaging learners in critical thinking. TechTrends, 43, 24-32. http://dx.doi.org/10.1007/BF02818172

Pathways to being WISE

“Learning environments that concentrate on conveying to students what scientists already know do not promote inquiry. Rather, an emphasis on inquiry asks that we think about what we know, why we know, and how we have come to know.” (National Research Council, 2000, p.5-6)

Simply, WISE projects aims to promote scientific inquiry by progressively working through with a student in a technology-enhance learning environment. Writing from SKI and WISE theorist strongly believes that learning is a personal and social construct where learners cycle through a process to assess, modify and revise current cognitive representations using technology-enhanced learning environment.

Key WISE prioritize are:

  • Making learning accessible

Many theoriets believe that students can better access information when it is more interesting and personal(Linn, Clark, & Slotta, (2003); Gobert, Snyder & Houghton (2002)). In addition to this definition, Gobert, Snyder & Houghton (2002) believe that in order to make learning more accessible, the discussed topic and the way in which it is presented should be appropriate for their individual age and skill level.

  • Making thinking visible

Another recurrent theme of the WISE pedagogy is to make thinking visible. Often, this materializes as comparing and contrasting previous assumptions, critiquing the views of others and using digital organizational tools and visualizers. More importantly, these visual modes of representation should be interactive.

  • Making learning a social process

Scholars who write about WISE believe that students should take advantage of social cognition. Students’ work should utilize asynchronous or synchronous tools to solicit peer review and response.

Given this premise, here are some modifications for a WISE project to allow the WISE priorities to be made more prominently. Using “Thermodynamics Challenge” as the cornerstone from the WISE library, a few supplementary activities are added and some modification to the platform of the WISE activity. More noticeably, the supplementary activities and change in the documenting platform promotes more visible thinking and ensuring a stronger peer learning culture.

Thermodynamic Challenge

This is a project-based assignment promoting a stronger understanding about the way in which heat moves and the role of insulation.

Introduction:

In the selected WISE project, it entices the students by reimagining their roles as consultants to recommend materials for cups to preserve the temperature of its contents.

Addition: Plicker Questions

In order to better identify students’ prior knowledge and misconceptions, quick response activities allow teachers to easily assess students’ thoughts. The advantage of using Plicker is that it generates a visualization of the recorded feedback in real time. This also supports learning as a group. First, educators can survey students about the kinds of materials for cups that they have used previously for hot and cold drinks. Then, after students complete the 1.5 activities in WISE (i.e. students are asked to choose to use the same or different material), ask students this identical question on Plicker, then show results and prompt a whole class discussion.

Modification: Google Documents

Instead of using the embedded digital notebook, students should complete their work on Google Docs as it can be easily shared and students can directly comment and annotate on the shared work. This also helps promote a network of peer support.

Then, students should continue to follow the WISE project outline and explore with the computer interactive simulation to assess the interaction between the different types of material and time. Using computer simulation is a time saving method to observe the efficiency of the preservation of heat. Next, students should continue to follow the WISE project outline to design, plan and run their experiment (i.e. 1.6 – 1.8).

Modification: Google Documents

Notably, this TELE is lacking further support for scaffolding during the knowledge reconstruction, reflection & negotiation stages. Students are tasked to review and annotate on two other students’ work. Using the ‘Suggestion’ mode, learners should comment and edit on other students’ work in order to  make thinking more visible and accessible. More importantly, Google Documents allow students to comment on specific ideas and details (i.e. lines/parts). Addition, this promotes the idea that learning is a social process. In order to enhance the knowledge reconstruction, teacher should also comment in suggestion mode to help bridge evidence to theory.

Addition: T-chart (Offline)

To make thinking more visible, students should create their own pre and post experiment T-chart to rank the efficiency of the preservation of temperature. Students should first record their predicted ranking and then re-rank the variables after their experiment. This organizer helps students compare their original thoughts and new findings.

Addition: Case studies

This WISE is lacking quality content scaffolds to help students rational their findings. Questions prompts are a good start, however, some students may fail to see the connections in the evidence. The goal of the conclusion of an inquiry is to “seek alternative hypotheses to explain anomalies or unexpected findings, and consider the applicability and impact of the findings to other organisms, theories, and domains” (Kim & Hannafin, 2011, p.406) To make better recommendations and to help fully explain their findings, students should review case studies about insulation in animals and homes. For example, students can watch short youtube clips (e.g. How an igloo keeps you warm; How do Whales, Penguins, and Polar Bears Keep Warm?)

Addition: Sharing Recommendations

Lastly, one area of improvement in the TELE is that students require more support to compare and contrast their recommendations. Again, students should review and assess their peers’ recommendations.

Ultimately, technology should be utilizied as an intellectual partner to promote scientific understanding and and discovery. In general, this WISE project that inquires about thermodynamics provides a sound foundation to investigate the relationship between different types of materials and temperature preservation. However, this WISE project on thermodynamics requires some modification in order to making thinking more visible and accessible and to enhance the social learning culture. To fully utilize this WISE project, educators can add content scaffolds and include more sharing and commenting options.

Discussion Questions

What are other digital tools to enhance learning via social means?

What are your thoughts about the relationship between scaffolding tools and WISE pedagogy?

Reference

Gobert, J., Snyder, J., & Houghton, C. (2002, April). The influence of students’ understanding of models on model-based reasoning. Paper presented at the Annual Meeting of the American Educational Research Association (AERA), New Orleans, Louisiana. This is a conference paper. Retrieved conference paper Saturday, October 29, 2013 from: http://mtv.concord.org/publications/epistimology_paper.pdf

Inquiry in Science and in Classrooms.” National Research Council. 2000. Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington, DC: The National Academies Press. doi: 10.17226/9596.

Kim, M. C., & Hannafin, M. J. (2011). Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice. Computers & Education, 56(2), 403-417.

Linn, M., Clark, D., & Slotta, J. (2003). Wise design for knowledge integration. Science Education, 87(4), 517-538. http://onlinelibrary.wiley.com/doi/10.1002/sce.10086/abstract

 

Video & Agumented Reality – Using mobile applications to supplement

The technology related to digital video is quite developed and allows for more interactive elements. In contrast to the Jasper videos, this design will combine video with mobile applications with agrumented reality overlays. More specifically, this design combines mobile application, argumented reality and video together. The mobile application allows students to submit real-time data. This information then creates the AR overlay on top of the video. Ideally, this would allow learners to view and manipulate information. The technology development leverages pedagogical concerns and makes the problem solving process more interactive, explicit and tangible. In essence, the mobile application acts as a log book for viewers. Moreover, videos can now be stored in cloud-based solutions, allowing easy access for global learners. Read below for a sample design of a revised educational ‘video’.

Design

  • Introduction: Sciencetific inquiry

In the video, it present a scientific inquiry question.

  • Activate prior knowledge

Viewers can contribute a public pool of knowledge about the topic by submission their information via a mobile application. A chart can be populated to help learners organize knowledge.

  • Inquiry information

Viewers can view and manipulate information via argumented reality overlay on their mobile device. More specifically, this information filter simultaneously allows students to view both the data and problem solving method. This may materialise as a note box or computer generated graphs. Students can also request a reorganization of data. They can easily compare and contrast information via charts and other graphic oraganizers.

  • Survey methods

Similar to the Jasper model, this design presents viewers with the ways in which other students or experts approach the inquiry question. Again, using mobile application via AR overlay, this design allow viewers to contribute a public pool of strategies to approach the inquiry question.

 

  • Trial & error & revision

Students can submit their plan via the mobile application. AI constructive feedback provides timely and accurate corrections. Learners will be allowed to revise their approach and resubmit. In the application, a public forum can be created to allow students to upload their ideas and review and critique their peers’ plans.

 

  • Extension

This inquiry should bridge to other authentic problems in the real world.

Notably, this design relies on Jonassen, Carr and Yueh’s (1998) definition of technology. The scholar suggests that technological tools are mere tools that aid learning by decreasing the cognitive load. More specifically, the tools are designed as storage solutions and compuation devices. In this design, the mobile application – i.e. AR overlay—assuages issues related to limited knowledge storage space and computation capacity. The mobile application helps decrease the cognitive load for data storage. Additionally, an AI chatbot is also included in the mobile application. According to Wang, Patrina & Feng (2015), virtual learning experience is more successful with chatbots because learners have access to a knowledge source and feedback.

Pedagogically, this design demonstrates traits from constructive theory. First, the embedded ‘know – wonder chart’ activates background knowledge and exposes possible misconceptions. Students engage in reflective learning where they can compare and constrast information. Second, cognitive apprentenship is present. The video progresses through a chosen inqiury model. Most importantly, this design is also consistent with social constructive theory. In Jasper’s model, the producers generate a graph to talk about the ways in which the general population approaches this a problem(Cognition and Technology Group at Vanderbilt, 1992a). Here, by using a forum, students can evaluate and help improve other students’ plans by providing feedback.

It is important to note that digital videos allow for constructivist affordance of learning. When used in combination of more efficent and interactive educational tools, videos can help assuage issues such as limited cognitive storage and reflection.

References

Cognition and Technology Group at Vanderbilt (1992a). The Jasper experiment: An exploration of issues in learning and instructional design. Educational Technology, Research and Development, 40(1), 65-80.

Jonassen, D.H., Carr, C. and Yueh, H.P. (1998) Computers as mind tools for engaging learners in critical thinking. TechTrends, 43, 24-32. http://dx.doi.org/10.1007/BF02818172

Wang, Y. F., Petrina, S. & Feng, F. (2015). Designing VILLAGE (virtual immersive language learning environment): Immersion and presence. British Journal of Educational Technology, 47(3), 1-20.

 

 

GRASP & TPACK

“New comprehension does not automatically occur, even after evaluation and reflection. Specific strategies for documentation, analysis, and discussion are needed.” (Shulman, 1987, p.19)

This quote is crucial to evaluating mathematical word problem solving skills. Students require direct instructions to support the development to skilfully extract information from word problems, identify missing attributes, select most approach analytical method and compute and make sounded conclusions. GRASP is an explicit metacognitive strategy that trains learners to effortlessly process word problems.

Using the GRASP Method to teach word problem solving skills

What is GRASP?

GRASP is a strategy to solve mathematical word problems. Below is the one of the many definitions of GRASP.

G – Give Information (i.e. operation signal words/ phrases)

Students are to extract information from a given word problem.

R – Required Information

Students are to identify parts that need to be solved.

A – Analyze (i.e. mathematical strategies)

Students are to select appropriate strategy (or strategies) to develop an answer.

S – Solve the question (i.e. computation)

Students are to use the select strategy (or strategies) to solve the question.

P – Paraphrase the answer

Students are to communicate their answer in a way that solves the problem.

 

Pedagogical Knowledge

Pedagogically, the GRASP method is a suitable framework to teach students how to solve word problems because this strategies shows thinking processes. The method helps make thinking visible by asking students to isolate and document components of the word problems. Linn (2000) believes that making thinking visible makes the metacogntive processes inspectable. In the case of GRASP, students can reflect upon their work and inspect the areas that led to an erroneous answer. For example, if it were a computation error, the analysis part would contain mistakes.

Teachers can clearly insepect how a student comprehends authentic word problems. Since students have to mindfully select appropriate analysis strategies based on given information, it mobilizes an integrated understanding of problem solving strategies. Moreover, authentic word problems make comprehension and problem solving accessible and relatable. Students are also more motivated to solve problems that were created by their peers.

Additionally, this strategy requires teaching practices such as scaffolding and modeling. Without this pedagogical strategy, students fail to independently apply the GRASP method. It is best to model as a whole class demonstration. Here, one can employ the cognitive apprenticeship. This pedagogical design helps foster problem-solving success by providing independent practice time. Moreover, this pedagogical awareness and experience helps promoting lifelong mathematical learning and success by installing a plausible approach to solve word problems.

Another pedgagoical consideration is about differentiation. The GRASP method enables all learners to find success in solving word problems. Some students find that advance operations (i.e. multiplication and division) are easy. In contrast, some students require direct operational signals to solve problems. This problem-solving approach allows educators to differentiate for slow or excelling learners. For example, teachers can modify the wording, include computation choices and provide sentence starters to fit the needs of their learners. Nonetheless, this depends on how well educators know about their students’ needs and strategies to support the needs.

 

Content knowledge

Shulman (1987) suggests that teachers serve “as the primary source of students understanding of content knowledge” (p.9). In the case of GRASP, teacher’s knowledge of signal words (i.e. math words and phrases that signals operations) and age-appropriate problems solving strategies influence how successful GRASP is. Explicit teaching of math vocabulary and computation strategies is key. Educators should be able to help students develop a strong repertoire of this knowledge. In this instant, educators need to develop content rich anchor charts to supplement students’ understanding of computation strategies and words that signal specific operations. Students also benefit when they are front-loaded with this information. These ideas are consistent with Shulman’s (1987) emphasis on the importance of teacher’s content knowledge. Without building a strong foundation of words and strategies, students fail to employ the GRASP method on more challenging word problems. Learners may also lack skills to develop their own problems.

 

GRASP & Technology

Although GRASP can be used without technology, simple word-processing knowledge would be beneficial. Educators can make set word problems more organized and attractive by printing off typed word problems and adding pictures. Additionally, to demonstrate that some problems are differentiated, teachers can place a picture on the opposite side.

Another key advantage of using the GRASP method is that educators can analysis the isolated parts of the word-problem solving process. Educators can digitally document students’ area of strength and or weakness. More specifically, teachers require higher digital competency to code an Excel sheet to automatically map student data and the evolving performance trends. For example, after values are imputed, the Excel can use color to highlight consistent errors and populate other visuals to show trends for student performance.

For learners, the computation part the GRASP can be digitized. For example, as students use GRASP, they can replace writing and drawing via technical means. More specifically, students can use Excel to make a graph or use Google drawing to visualize and manipulate variables to improve computation efficiency and accuracy. This is consistent with Jonassen’s (2000) claim. He believes that “that the most productive roles for media are as computation and memory tools for off-loading unproductive cognitive task that may interfere with knowledge construction by the learner.” (Jonassen 2000, p.33) Furthermore, students can also discuss their GRASP methods on student forums to extend their and extend their thinking.

Food for thought

In Mishra & Koehler (2006), although the overlapping circles appeal to be a useful method to talk about integrating these different types of knowledge, it may not accurately represent the extent of each type of knowledge. Rather, a power map may provide more information. In a sense, each example has its own power map. Here is what the GRASP model may look like:

Visibly, the success of GRASP relies heavily on pedagogical and content knowledge.

A follow up question is how educators evaluate whether this is a ‘good’ mix of Msihra & Koehler’s idea of TPACK? Are these variations dependent of content?

 

References

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers college record, 108(6), 1017.

Jonassen, D. H. (2000). Computers as mindtools for schools, 2nd Ed. Upper Saddle River, NJ: Merrill/ Prentice Hall. Retrieved from Google Scholar: http://scholar.google.com/scholar?q=Jonassen+mindtools&ie=UTF-8&oe=UTF-8&hl=en&btnG=Search

Linn, M.C. (2000). Designing the knowledge integration environment. International Journal of Science Education, 22(8), 781-796.

Shulman, L.S. (1987). Knowledge and teaching. The foundations of a new reform. Harvard Educational Review, 57(1)1-23.

Organized Chaos

Knowledge formation is a personal and social process. Intrapersonal and interpersonal and human-technology interactions influence knowledge construction. Moreover, knowledge is a fluid entity where the relationships between these variables exist as synergistic interactions. Borrowing Jonassen & Carr and Yueh’s (1998) idea about technology sharing cognitive responsibilities, digital tools should target specific cognitive load. Designers should consider learning experience that is student-centred with technological tools to help students establish relationship between concepts. It should allow student the flexibility to manipulative variables and to constantly reorganize constructs. The context should increase student opportunities to practice and test their knowledge (i.e. analysis thinking patterns – i.e. visualization and simulation). It should make learning (i.e. constructing relationships among variables) more favorable and efficient. It should consider learning activities that allow for near transfers of conceptual knowledge where students apply their understanding (i.e. problem-based learning).

Designers of learning experience can:

  • Isolate cognitive load that technological tools are responsible for.

(e.g. data storage, organizational and or visualization tools)

  • Isolate cognitive processes that require more support.

(e.g. information processing and analytical tools for reflection)

  • Identify opportunities for learners to socialize.
  • Integrate these educational tools and scaffold students’ use according to their competencies.

References

Jonassen, D.H., Carr, C. and Yueh, H.P. (1998) Computers as mind tools for engaging learners in critical thinking. TechTrends, 43, 24-32. http://dx.doi.org/10.1007/BF02818172