On my last prac week, I had an interesting conversation with my mentor teacher about curriculum. We discussed the silliness of the IB physics curriculum (the best analogy I can think of would be trying to drink physics from a fire-hose) but found we had differing ideas about the most fitting content for a secondary school physics class and really, the purpose of introductory physics altogether. Coming from a physics research background, I have always tended to think that the most fitting content for an introductory class is mechanics and some basic electromagnetism with maybe a little thermodynamics thrown in. It’s what you do at uni, and it teaches problem solving and critical thinking skills, not to mention a basic awareness of what’s going on around us in everyday life. My mentor’s take is that you should try to cover a lot more content than that, including optics and a range of topics relevant to medical physics because students find it interesting and it’s also relevant to their lives. This brings up the provocation: what will my students want and need from me? I understand the point that students want to cover more content, to get to the more “interesting” stuff, I just wonder what cost it comes at. Covering too much content is inevitably going to mean you don’t go into depth, and risk not addressing students’ non-scientific conceptions of physics. It’s something I still find myself thinking about weeks later. Maybe the best answer lies in having a true inquiry based classroom where the kids get to explore concepts and the curriculum emerges. Problem is, the BSSS won’t ever sign off on that. Will I be allowed to be the teacher I want to be?
Developers of physics simulations promote them as a valuable tool for interactive engagement (IE) (Wieman & Perkins, 2005), a framework for teaching physics that is well-established in the literature as being superior to traditional methods (Hake, 1998; Redish & Steinberg, 1999). There have been many studies on the effectiveness of physics simulations, yet their status as a tool for promoting conceptual change in physics courses remains controversial. Unfortunately, the majority of investigations have been case studies, with relatively few experimental studies undertaken. While the type of simulation and the contexts in which they are used are certainly important, the question remains as to whether they can be used effectively in the support of interactive engagement teaching strategies. I argue that simulations can be used effectively in support of IE methods as a tool for aiding observation, but that the implementation and possible side-effects of their use need to be considered carefully.
The term interactive engagement refers to a range of different teaching techniques that use “heads-on (always) and hands-on (usually) activities” (Hake, 1998, p. 65) and which emphasize the construction of knowledge by students and the teacher’s role as a facilitator of learning. They also directly address students’ pre-existing non-scientific conceptions (Knight, 2004). Hake (1998) performed a meta-study of introductory physics courses, finding that traditional methods (instructor-centric teaching with lectures, tutorials and laboratories) tended to produce remarkably consistent and embarrassingly poor results on the force concept inventory (FCI), a test developed by physics education researchers to probe understanding of Newtonian mechanics. His measure of comparison was the percentage of total possible improvement, or normalized gain[i]. He found that traditional methods produced a consistent normalized gain of approximately 23% on the FCI (e.g. an average student entering the class with a 30% would improve to a 46%) after a semester of instruction in mechanics. This result was independent of pre-test scores and instructor. IE methods consistently led to normalized gains in the region of 30-70% with an average of 48%, a two standard deviation effect. A further problematic feature of traditional methods is that they consistently promote counterproductive beliefs about physics. Redish and Steinberg (1999) used a test designed to discover student attitudes on a scale of “independence/authority, coherence/pieces, and concepts/equations,” (p. 29) and found that a single semester of a traditional physics course led to a regression from “expert” (p. 33) beliefs of approximately one standard deviation. Meanwhile, IE methods resulted in improvements of 2.5 standard deviations.
IE physics courses are typically ICT intensive, with the most common technologies being data loggers, video analysis software, motion detectors, force probes and computers (Knight, 2004). For resource-poor physics classrooms, simulations appear to be an attractive alternative to the purchase of extra lab equipment and the development of new activities. Or are they?
The literature on the effectiveness of physics simulations is full of controversy. Some studies have suggested that physics simulations are powerful agents of conceptual change (Keller, Finkelstein, Perkins & Pollock, 2006; Squire, Barnett, Grant & Higginbotham, 2004; Zacharia & Anderson, 2003), while others have shown no benefit over alternative methods (Ronen & Eliahu, 2000; Steinberg, 2000). The vast majority of these studies suffer from significant research design flaws, e.g. failing to adequately isolate the method of instruction in Squire, Barnett, Grant and Higgenbotham (2004), or having been done on far too small of a scale to find measurable effects, as in Zacharia and Anderson (2003). Effectiveness studies have almost exclusively focused on a comparison with traditional methods. An exception is Steinberg (2000) who showed no difference in effectiveness, compared with IE methods. This study also suggested – based on casual, qualitative observations – that simulations may promote authoritarian views of physics. Unfortunately, no quantitative research has investigated this issue.
A recent study by Trundle & Bell (2010) used a quasi-experimental design to test the effectiveness of computer simulations in teaching pre-service teachers about lunar phases. They compared three groups, the first of which used observations of nature, the second computer simulations for observation, and the third, a combination of the two. Observations were supported by a research-backed IE teaching method. They found no measurable differences in conceptual understanding between these groups. While at first this seems a disappointing result, it is strong evidence that simulations, when used to promote well-researched IE style teaching methods, can replace other types of observation that may be difficult or impossible in a resource-limited environment. It is also worth noting that all three types of observation resulted in the average study participant obtaining mastery of the concept of lunar phases.
At this point it is worth considering how, from a theoretical perspective, conceptual change is brought about in physics. It is well-understood that students come into an introductory physics class with very strong alternative (non-scientific) conceptions of physical processes (Halloun, Hestenes, 1985a), which are often very similar to various non-scientific beliefs which have prevailed through much of history (Halloun, Hestenes, 1985b). A brief look at human history indicates how difficult it is to break these conceptions. A first step is to use these conceptions to make a prediction about a physical phenomenon, followed by a careful observation. This will tend to put students into a state of cognitive dissonance (Tao & Gunstone, 1999) when they attempt to explain their observation, which can in turn lead to the adoption of new, scientific conceptions. This is the primary mechanism of IE techniques (Wells, Hestenes & Swackhamer, 1995). Tao & Gunstone (1999) found that when physics simulations are used to induce cognitive dissonance, they tended to promote conceptual change, but the change was difficult to maintain and generalize.
Used in isolation, physics simulations are unlikely to be any more effective than traditional methods. They are, however, a technology that appears to be very good at promoting the careful observation of visualisations of physical phenomena. It seems likely that in this role, they can play a very important part in the “predict-observe-explain” cycle (Tao & Gunstone, 1999, p.859; Trundle & Bell, 2010). In an IE classroom, their use fits naturally as an activity after students have been asked to make a prediction of the physical phenomenon in question. The observation phase can then be followed with discussions where alternative conceptions are explicitly confronted and by collaboration among students to build new models to explain their observations which can then be tested. Where possible, other visualisations of phenomena should also be used to support connections to the physical world and aid generalization of the concept. Not all simulations are created equal, and they need to be measured against criteria assessing their ability to confront common alternative conceptions and to support considered observation. We should also assess their likelihood of promoting authoritarian views of physics, and avoid those that promote a rapid-fire trial and error approach geared towards obtaining the “correct” answer. Clearly, our understanding of the role physics simulations can play in IE teaching methods needs further development, especially for physics topics with a known high-resistance to change. Finally, further research is needed on how physics simulations affect attitudes towards physics and whether or not they undermine the beneficial effects IE methods have on these attitudes.
Hake R (1998) “Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses,” American Journal of Physics, 66(1):64-74.
Halloun I & Hestenes D (1985a) “The initial knowledge state of college physics students,” American Journal of Physics, 53(11): 1043-1055
Halloun I & Hestenes D (1985) “Common sense concepts about motion,” American Journal of Physics, 53(11): 1056-1065
Keller C, Finkelstein N, Perkins K & Pollock S (2006) “Assessing the effectiveness of computer simulation in introductory undergraduate environments,” in McCullough L, Hsu L & Heron P (Eds.), AIP Conference Proceedings Volume 883: 2006 Physics Education Research Conference, 121-124, Syracuse, USA: American Institute of Physics
Knight R (2004) Five Easy Lessons: strategies for successful physics teaching, San Francisco, USA: Addison Wesley
Redish E & Steinberg N (1999) “Teaching physics: figuring out what works,” Physics Today, 52:24-30
Ronen M & Eliahu M (2000) “Simulation – A bridge between theory and reality: The case of electric circuits,” Journal of Computer Assisted Learning, 16:14-26.
Squire K, Barnett M, Grant J & Higginbotham T (2004) “Electromagnetism supercharged!: Learning physics with digital simulation games” in Kafai Y, Sandoval W, Enyedy N (Eds.), ICLS ’04 Proceedings of the 6th international conference on Learning sciences, 513-520, International Society of the Learning Sciences.
Steinberg R (2000) “Computers in teaching science: to simulate or not to simulate?” American Journal of Physics, 68(7):S37-41
Tao P & Gunstone R (1999) “The Process of Conceptual Change in Force and Motion during Computer-Supported Physics Instruction,” Journal of Research in Science Teaching, 36(7):859-882.
Trundle K & Bell R (2010) “The use of a computer simulation to promote conceptual change: a quasi-experimental study,” Computers and Education 54: 1078-1088
Wells M, Hestenes D & Swackhamer G (1995) “A modelling method for high school physics instruction,” American Journal of Physics, 63(7): 606-619
Wieman C and Perkins K (2005) “Transforming Physics Education,” Physics Today, 58:36-48
Zacharia Z & Anderson O (2003) “The effects of an interactive computer-based simulation prior to performing a laboratory inquiry-based experiment on students’ conceptual understanding of physics,” American Journal of Physics, 71(6):618-629.
[i] The normalized gain is defined as (Post-test % – Pre-test %)/(100% – Pre-test %)
Wayne is disappointed in his students’ lack of deep engagement with the work in his class. He has observed two broad groups of students in his classes. The first of these shows classic signs of disaffection or the opposite of engagement (Skinner & Belmont, 1993). They don’t want to be in his class, may be withdrawn and/or openly rebellious and feel depressed or anxious about having to be there (Skinner & Belmont, 1993). The second group of students is superficially engaged, only wanting to know the “correct answers.” Their primary concern is obtaining a good mark in his class and scoring well on end of school exams to aid entry to the nearby university. Their motivation for learning has an “external perceived locus of causality” (Ryan & Deci, 2000a, p. 59), i.e. their motivation for learning has not been internalized or assimilated with their own personal values and interests.
Self-determination theory, or SDT, originated as an empirical model of motivation (Ryan & Deci, 1985). It postulates that there are three primary psychological needs that, when satisfied, tend to facilitate higher levels of motivation. These needs are competence, autonomy and relatedness. Competence refers to a students’ perceived ability to understand and achieve a goal. Autonomy is the opportunity for self-direction and self-determination. Relatedness refers to feelings of personal social connection in relation to the internalization of values and regulations (Ryan & Deci, 2000b).
Beyond a simple dichotomy of amotivation vs. motivation or even a trichotomy of amotivation, extrinsic and intrinsic motivation, SDT proposes that there is an effective continuum of extrinsic motivation, along a scale of autonomy (Deci & Ryan, 2000b). Higher levels of motivation and engagement are associated with a higher degree of internalization of the reasons, values and importance of a topic. At one extreme, extrinsic motivation shares many of the characteristics of intrinsic motivation, namely volition and value, but remains extrinsic because the motivation is seen to come from a separable outcome (not from simple enjoyment of a task as with intrinsic motivation) (Deci & Ryan, 2000b). At the other end of the spectrum, motivation is a result of external demands or rewards and is controlling.
Higher degrees of internalization of motivation and values have been associated with a myriad of beneficial outcomes, not least of which (and perhaps the most important for Wayne’s students) is a lower incidence of drug and alcohol abuse (Knee & Neighbours, 2002). Other outcomes include greater engagement (Reeve et. al., 2004), higher performance at school (Miserandino, 1996) and on standardized tests (Skinner, Wellborn & Connell, 1990).
As an educator, the most important point for Wayne is to discover practical tools and ideas as to how to facilitate motivation in his students. Wayne can support autonomy by providing choice to his students, encouraging self-starting, minimizing controlling behaviours and by clarifying the relevance of learning outcomes for his students (Assor, Kaplan & Roth, 2002). Assor, Kaplan and Roth (2002) found that the best teaching behaviour for predicting student engagement is fostering relevance. That is to say, the single most important thing Wayne can attempt to do is to help students understand the contribution that their schoolwork has to the realisation of their personal goals and interests. Helping students understand the relevance of his classwork is intertwined with nurturing relatedness. To be able to effectively promote relevance, Wayne needs to get to know his students personally to understand what they value and are interested in (Reeve, 2002). If he is able to demonstrate that he cares about his students, they will be more likely to value his input and give his enthusiasm for the subject more weight. Finally, Wayne can support competence by providing structure for his class (not to be confused with attempting to control them and take away their autonomy). He can do this by making his expectations for the class and their learning outcomes clear, providing learning tasks that challenge his students but for which success is attainable, and by providing relevant and timely feedback on assessment (Reeve, 2002).
Assor, A; Kaplan, H & Roth, G (2002) “Choice is good, but relevance is excellent: autonomy-enhancing and suppressing teacher behaviours predicting students’ engagement in schoolwork,” British Journal of Educational Psychology, 72:261-278
Deci, E, & Ryan, R (1985) Intrinsic motivation and self-determination in human behaviour, New York: Plenum
Deci, E & Ryan, R (2000a) “Intrinsic and extrinsic motivations: classic definitions and new directions,” Contemporary Educational Psychology, 25: 54-67
Deci, E & Ryan, R (2000b) “Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being,” American Psychologist, 55(1): 68-78
Knee, C & Neighbors, C (2002) “Self-determination, perception of peer pressure, and drinking among college students,” Journal of applied social psychology, 32(3):522-543
Miserandino, M (1996) “Children who do well in school: Individual differences in perceived competence and autonomy in above-average children,” Journal of Educational Psychology, 88:203-214.
Reeve, R (2002) “Self-determination theory applied to educational settings,” in Deci, E & Ryan, R (Eds), Handbook of self-determination research, 183-203, Rochester: University of Rochester Press
Reeve, R; Jang, H; Carrell, D; Jeon, S & Barch, J (2004) “Enhancing Students’ Engagement by Increasing Teachers’ Autonomy Support” Motivation and Emotion, 28(2):147-169
Skinner, E & Belmont, M (1993) “Motivation in the classroom: reciprocal effects of teacher behaviour and student engagement across the school year,” Journal of Educational Psychology, 85(4):571-581
Skinner, E; Wellborn, J & Connell, J (1990) “What it takes to do well in school and whether I’ve got it: a process model of perceived control and children’s engagement and achievement in school,” Journal of Educational Psychology, 82(1):22-32
So, I’ve apparently had a catastrophic failure on the trying not to kick and scream front, mentioned in my first post on this topic. Apologies to all the IWB fanboy/girls, not to mention all the people just sick of hearing me whinge (LOL, poor Meg); part of my disdain is connected to the cost, the rest is largely due to how I’ve seen them used so far in the classroom (damn you, ClickView). They’re just a tool after all, and surely I can find some good uses. What I really want to know is: how can I use an IWB effectively in my role as a facilitator of learning and not in the teacher-centric transmission style of teaching?
There has been a lot of work done on investigating the different types of pedagogies that IWBs can promote. Kearney and Schuck (2008) performed a study investigating some of these in Australia. They found that IWBs were often used to promote “whole-class interactions” (p. 10). They acknowledged, however, that these were often teacher-centric and a “traditional authoritarian interaction” (p. 10). Not exactly what I’m after, in terms of promoting interactive engagement. On a more interesting note, they mention that IWBs could be used to reinforce the relevance of topics being taught, as real world applications were readily available through the IWBs interface with the web. That’s all well and good, but how does this differ from a standard projector, besides saving the teacher two steps to their computer to use the mouse?
A study by Hennessy, Deaney, Ruthven and Winterbottom (2007) investigated strategies for using IWBs to promote participation among students in secondary school science. They studied the use of IWBs by two experienced teachers who designed lesson plans carefully to integrate the use of IWBs into their teaching style. Note the order: good pedagogy then integrated technology where it makes sense. Both teachers attempted to focus on getting students to interact with the IWB in a hands-on manner. In practice, the researchers noted that actual student interaction with the IWB was extremely limited, with a maximum of two students physically interacting with the whiteboard during any lesson they observed, for brief periods. Time constraints were identified as the predominant hindrance to student participation.
I’m willing to admit that I can see using an IWB to get students playing with a physics simulation, for instance, or for demonstrating how a piece of software works while students play along on computers in groups. It seems it may be possible to make IWBs “interactive” after all, it might just take some creativity to get there. I hope that in my classroom, this will be when the pedagogy requires it rather than the other way around.
Epic Fail [Online image] Retrieved from http://www.sav3rio.com/2010/02/epic-fail/
Hennessy, S , Deaney, R , Ruthven, K and Winterbottom, M (2007) ‘Pedagogical strategies for using the interactive whiteboard to foster learner participation in school science’, Learning, Media and Technology, 32: 3, 283 — 301
Kearney, M, and Schuck, S (2008) “Exploring pedagogy with interactive whiteboards in Australian schools,” Australian Educational Computing, 23(1): 8-14
For argument’s sake, let’s say for the moment that I believe that IWBs actually do have a small statistically significant effect on student motivation and engagement (I can feel my nose growing as I type). Is it worth the cost? Or even better, what other (cheaper!) alternatives are there to encourage engagement? I’ll be a bit selfish and focus on physics and mathematics here, because that’s where my knowledge base and interest is.
IWBs vary a lot in price. Many of the ones I’ve seen in classrooms recently fall in the price range of US $4000-$6000 (I hate to think what they cost in Australia!), not including the cost of a computer to power it. The ones at my prac school appear to be at the upper end of that range. They’re a slightly better deal when bought en masse, but still, they’re not exactly cheap. Even their biggest fans acknowledge cost as a set-back (Lipton & Lipton, 2000). What other technologies could I purchase for that sort of cash? For a physics class, I could buy a class set (by which I mean around eight) of cheap, functional computers and have money left over for some digital lab equipment to use with them (e.g. wiimotes and a digital video camera). Better yet, for half the cost of a replacement bulb for the projector, I could buy a class set of small mobile (albeit analogue, LOL) whiteboards that would put an IWB to shame in terms of the interaction they would facilitate in the classroom. Think of the ass-kicking pedagogy that such a simple tool supports. Students work in small groups, sharing ideas, peer instruction, the lot, all for $20 (or if you live in the US, $2).
You might (fairly) ask whether there is any research to support my implied thesis that these tools could lead to better learning outcomes. The answer is a resounding hell yes. In physics, there is a mountain of research supporting that an appropriate use of these kinds of tools, for instance, in a modeling context, can lead to hugely enhanced learning outcomes. Quarter of a standard deviation effects, be damned, try two plus. See, for example, Wells, Hestenes & Swackhamer (1995) or Hake (1998).
Hake R. (1998) “Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses,” American Journal of Physics, 66(1): 64-74
Lipton, M and Lipton, L (2010) “Enhancing the radiology learning experience with electronic whiteboard technology,” American Journal of Roentgenology, 194: 1547-1551
Wells, M; Hestenes, D and Swackhamer, G (1995) “A modelling method for high school physics instruction,” American Journal of Physics, 63(7): 606-619