Author Archives: jwlewis

T-GEM, PhET, and Water Conductivity

Many concepts are difficult for students to understand without some form of visualization to aid the description. This week I have integrated T-GEM with a water conductivity PhET Simulation to create a lesson activity which can address misconceptions. A regular misconception that students have is that pure water conducts electricity. By the end of this lesson students should be able to communicate what makes water conductive.

Step 1: Introduction

-Students form groups of 2-3, each group will have a computer, paper, and writing utensil

-Review as a class:

1 – What is electricity? What is flowing?

2 – How do we make electricity?

3 – What is concentration (with respect to dissolved solids)?

4 – How could we make things more or less concentrated?

Step 2: Generate

Have students as a group generate ideas around the following key questions:

1 – Is water conductive?

2 – How does electricity move in water?

3 – Would dissolving solids in the water change its properties?

Each group will write their predictions down on a piece of paper.

Step 3: Evaluate

Have groups use PhET Simulation “Sugar and Solutions” to investigate water conductivity.

Ask students to test if their predictions are correct.

Step 4: Modify

Ask students to create a situation where their new knowledge of water conductivity could be useful.

(The use of Makey-Makeys can be used so students can make an apparatus which physically uses water conductivity to control a computer)

Step 5: Reflect

Have students revise their original ideas and together formulate the main points of water conductivity.

References

Friedrichsen, P. M., & Pallant, A. (2007). French fries, dialysis tubing & computer models: Teaching diffusion & osmosis through inquiry & modeling. The American Biology Teacher, 69(2), 22-27.

Khan, S. (2010). New Pedagogies on Teaching Science with Computer Simulations. J Sci Educ Technol, 20(3), 215–232. http://doi.org/10.1007/s10956-010-9247-2

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

E-FOLIO

https://blogs.ubc.ca/533james/

Knowledge construction in the real world

Traditionally, educational professionals believed that knowledge in math or science must be constructed by first learning the simple mechanical and fact-based aspects before being able to integrate these fundamentals into real-world problems. While it may make sense to construct a building by first focusing on fundamental pieces such as a foundation and framing, this method may be too simplified to apply to students who are embodied in a world with a plethora of problems to be solved, some of which they may never have experienced before. Carraher et al (1985) looked at math skills in the practical world and discovered that youth with very little formal education developed successful strategies to deal with real life mathematical problems in a market. The youth could successfully solve 95% of problems in the informal market setting while only being able to successfully solve 73% of the problems given to them in a formal test setting. “It seems quite possible that children might have difficulty with routines learned at school and yet at the same time be able to solve the mathematical problems for which these routines were devised in other more effective ways” (Carraher et al, 1985). Thus, as educators it can be useful to use real-life problems in the world to help students gain more applicable and effective knowledge.

Two ways in which students can use real-life experiences to guide their learning is through networked communities such as GLOBE and Exploratorium. In the GLOBE project, scientists are linked with teachers and students to gather data from around the world (Butler & MacGregor, 2003). Students are taught data collection techniques and can visually display their and other’s collected data to analyse and interpret. An example of such is looking at the carbon cycle in different biomes; students collect topsoil data from their region and compare it with data from other students in different parts of the world. With this program, students can directly participate in global knowledge generation on a global scale. Further, Exploratorium presents a virtual museum which allows students to interact and learn with interactive tools, hands-on activities, apps, blogs, and videos to learn about science. “Many innovative educational applications, tools, and experiences are being specifically designed to capture the interests and attention of learners to support everyday learning” (Hsi, 2008). Such tools allow students to generate knowledge in and out of the classroom as the line between formal and informal education becomes blurred. The goal from informal learning is to create a passion for life-long learning in students. If students can self-motivate, knowledge construction can become limitless.

Butler, D.M., & MacGregor, I.D. (2003). GLOBE: Science and education. Journal of Geoscience Education, 51(1), 9-20.

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.

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

Embodied learning and gestures

Embodied learning revolves around the notion that it is not just the brain participating in learning activities, rather the whole body participates, interacts, and manufactures new concepts (Winn, 2003). Winn works to defeat the notion that the mind and body are separate entities, rather the interactions we have with our environment is key to the learning process. Removal of environmental learning experiences works to limit student’s ability to adapt with the environment and therefore form a more complete learning experience. Winn (2003) encourages educators to create a “framework that integrates three concepts, embodiment, embeddedness and adaptation.” This embodied learning can be extended to artificial environments where students actively engage and become “coupled” (Winn, 2003). A person in a coupled learning environment actively engages and interacts through problem solving and discovery learning.

The use of mobile technology can allow students to become coupled learners with artificial environments. “They also have the potential to establish participatory narratives that can aid learners in developing a contextual understanding of what are all too often presented as decontextualized scientific facts, concepts, or principles” (Barab & Dede, 2007). Mobile technologies can allow students to become fully immersed in virtual scenarios where they must participate in scientific processes, or partially immersed where they use mobile technology to aid a real-life investigation. Barab & Dede (2007) highlight the use of game-based technologies to target academic content learning in more embodied and integrated formats.

Zurina & Williams (2011) helped my understanding of embodied learning in the classroom by analyzing how children may gesticulate to solve problems they are working on. Gesticulation is required by these children as they work integrated with their bodies and environment in the learning process. Without realizing it, as I explored this topic I realise that I model embodied behaviour to my students through instruction. For example, when analysing linear and polynomial graphs, I teach students to use the left arm rule to determine if the leading coefficient is positive or negative (one holds their left arm up to recreate slope of the graph; if it is easy the slope is positive, if it is difficult to contort your arm in such a way the slope must be negative).

Are there other embodied actions which help teachers reach their students?

Are you performing gestures which aid in learning without knowing it?

Barab, S., & Dede, C. (2007). Games and immersive participatory simulations for science education: an emerging type of curricula. Journal of Science Education and Technology, 16(1), 1-3.

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, 2013. Retreived from: http://www.hitl.washington.edu/people/tfurness/courses/inde543/READINGS-03/WINN/winnpaper2.pdf

Zurina, H., & Williams, J. (2011). Gesturing for oneself. Educational Studies in Mathematics, 77(2-3), 175-188.

Synthesis

TELES present an engaging and relevant way to encourage student learning. In Module B, we took a look at four models of TELEs which help to bridge the gap between real-world science and the textbook-based model many science teachers have become reliant on. These models are T-GEM, Anchored Instruction, SKI/WISE, and LfU. Some of the major similarities between these models are collaborative approaches, solving real-world problems, working with real-world data sets, and scaffolding new observations with student preconceptions. Such approaches strive to break the cycle of textbook and fact-based learning which do little for generating a realistic view of science, motivating students, and developing critical thinking skills. The exploration of these four models has greatly increased my confidence in building an effective science classroom. These topics are a refreshing way to integrate high level cognitive skills into a science classroom and will greatly aid my ability to design and run science classes which can remain interesting, relevant, and applicable to students.

While working through this module I still struggle to think of creative ways to include these four models into my mathematics instruction. Apart from data analysis and the use of math in multi-disciplinary problems, I remain lost in how to change my mathematics instruction in similar constructive ways as in science. I find the access to online Math instructional aides to be limited in ability and scope. As the new BC Ministry of Education rolls out to all the grades, learning activities such as the four which we looked at in this module will become valuable assets to fulfill curricular and core competencies.

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

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. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/ 10.1002/1098-2736(200103)38:3<355::aid-tea1010>3.0.CO;2-M

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

Williams, M. & Linn, M. C.(2002) WISE Inquiry in Fifth Grade Biology. Research in Science Education, 32(4), 415-436.

T-GEM and Atomic Structure

From previous experience in teaching the chemistry portion of Science 9, it is apparent that Isotopes remain a difficult concept for many students to grasp. It is very common to see the same mistakes emerge on assignments and tests and remains a persistent issue for many students.

Using the concepts of TGEM (Khan, 2007), I have found generated an activity which works to teach atomic structure and isotopes using the Bill Nye Video and PhET simulation below.

Bill Nye: Atoms and Molecules

PhET Simulation: Build-an-Atom

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

LFU with Space Science

The Learning for Use (LFU) framework consists of a three-step process consisting of Motivation, Knowledge Construction, and Knowledge Refinement (Edelson 2001). I have chosen to apply such a framework to the grade 10 Space Science unit about the big ideas of the Big Band Theory and star system formations. There are several technologies which can aid in the LFU framework implementation with this unit such as Stellarium, and Universe Sandbox. Stellarium can be used to analyse stars and planets with scientific accuracy and locate these phenomena in the sky. Universe Sandbox on the other hand allows to interact with planets and star systems, many of which begin as factual, observed systems. This interaction can be anything from adjusting climate, rotational speed, to creating new planets, moons, and collisions.

Motivation

Both technologies include factual information about celestial bodies around us. Students tend to have a natural curiosity about the world around them and these programs can help to scaffold their previous knowledge. Looking at the gravity (and in comparison, their weight) on different planets can begin to have students gain a deeper understanding to the scale of celestial bodies while linking it to their experiences on Earth. The further affordances of Universe Sandbox allow students to create the scenario of placing planets close to each other to see what the result would be (i.e. which would be the satellite, Earth or Mars?). The ability to play with this content means we can effectively merge motivation with knowledge construction.

Promoting Knowledge Construction

Through interacting with their previous knowledge, students can build new pathways and commit new information to memories. The more interaction with such tools can provide students with a greater understanding of how start systems function and can be perturbed. Being able to physically change variables of celestial bodies in Universe Sandbox allows students to physically interact with such concepts and to promote new knowledge construction. Some of the most notable experiences with such a program, is when students discover they can collide planets with asteroids, moons, other planets, and black holes. In an interesting parallel with the CERN Supercollider, students report on gaining interest and knowledge quite rapidly when they can smash celestial objects together.

Refining Knowledge

“Reflection and application both make important contributions to the inherently cyclical nature of learning” (Edelson, 2001). Universe Sandbox allows students reflect on previously learned concepts on orbiting celestial bodies to apply this knowledge to construct new star systems; very quickly students realize that star systems are not easily constructed. This process of knowledge application can help reinforce knowledge for future retention and use.

I find that the process of LFU can be easily applied to games which keep students learning and exploring through their own self-interest. Using large online databases, games are beginning to merge scientific accuracy with entertainment. This creates a golden opportunity for technology in the classroom which can spark the learning process.

References

Photosynthesis: Where do Plants get Energy?

The WISE project I chose to further develop was the “Photosynthesis” project originally created by Kelly Ryoo (ID: 2276). This project has several learning and response activities for students to interact with on the topics of energy transformation with Photosynthesis and how it pertains to an herbivore’s energy consumption. The project was aimed at students 6-8 and requires 4-5 hours to complete. The lesson asks students to make predictions, scaffold on previous knowledge, and contains many vocabulary definitions for words which students may be learning. In many of the lessons which I previewed, students were asked to link new concepts with their own experiences. The WISE projects, including “Photosynthesis” play a valuable role in providing a vehicle to integrate knowledge and scaffold it to student’s own experiences (Linn et al 2003).

One problem with this lesson is the need for these students to have prior knowledge about the topic they are learning; on several circumstances, students were asked to answer a multiple-choice question with no prior knowledge or experience with the vocabulary terms. Formative assessments in a lesson such as this one require students to first experience the content before being asked to make a composition, answer an inquiry question, or take a multiple-choice knowledge check. My efforts in this WISE project was to place these interactive tools in more appropriate places as well as to improve the scientific accuracy of the lesson. One further modification which can be made in the future would be to better address misconceptions around how plants gain the majority of their matter. I was unsatisfied that after this lesson, students may still believe that a plant or tree’s mass would mainly come from soil nutrients rather than acquired Carbon Dioxide in the air. Students bring to class many different fallacies about the topics which we learn in class (Linn et al 2003) which must be addressed before new knowledge can be gained (Brown & Palincsar 1986).

References

Brown, A., Palincsar, A. (1986). Guided, cooperative learning and individual knowledge acquisition. Center for the Study of Reading. Cambridge, MA. Retreived from: http://files.eric.ed.gov/fulltext/ED270738.pdf

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

Anchored Instruction Hybrid Learning?

Anchored instruction remains a fascinating subject which employs the strength of integrating problem solving with instruction to improve student success, interest, and achievement when it comes to working with complex real-world problems. These problem-rich environments allow students to engage in learning through exploration of complex problems and ideas (Cognition and Technology Group at Vanderbilt [CTGV], 1992a). As shown by Shyu (2000), elementary students in Taiwan demonstrated increased interest, attitudes towards math, and achievement in problem-solving assessments. With such correlations using video-based anchored instruction, it would be interesting to discover the effects of increased interaction on students using more sophisticated technology such as videogame-style anchored instruction. Contrary to the effects seen in Taiwan, Park & Park (2012) discovered that the freedom of anchored instruction may leave students to develop incorrect knowledge when solving engineering problems. It stands to reason that the careful and deliberate implementation of anchored instruction at certain areas in education may be required to extract the most positive impact for students.

The Anchored Instructional approach suggests that “instructional goals for mathematics and science need to be quite different from the ones illustrated by typical test items that focus primarily on component skills” (CTGV 1992a). Are the effects of the Anchored Instruction studies a result of students using previous and classically taught ‘component skills’ in a new and more integrated approach? Would students who worked with Anchored Instruction from the beginning of their education have the same achievement and results? It would be very interesting to see how this approach works for the long-term benefit of children.

I believe that we have many tools at our disposal to bring Anchored Instruction into modern instruction. Rather than replacing current models of instruction, the supplementation of such models can help to bring students and teachers enrichment in both instruction and learning. A gradual implementation would be needed as such resources are assuredly difficult to construct, and deliver in a meaningful way.

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.

Park, K., & Park, S. (2012). Development of professional engineers’ authentic contexts in blended learning environments. British Journal of Educational Technology, 43(1), E14-E18.

Shyu, H. Y. C. (2000). Using video‐based anchored instruction to enhance learning: Taiwan’s experience. British Journal of Educational Technology, 31(1), 57-69.