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This thesis investigates the use of concept cartoons and self-explanation prompts to enhance sixth-graders' ability to interpret data and draw valid conclusions in a physics task. The study found that children in the concept cartoon and self-explanation condition needed fewer comparisons to draw a conclusion than those in the control and concept cartoon-only conditions.
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Bachelor Thesis Psychology Instructional Technology (ILO) First attending: Dr. P. Wilhelm Second attending: Dr. A.W. Lazonder
De effectiviteit van concept cartoons en self-explanations voor het bevorderen van vaardigheden in data interpretatie en theorie-revisie bij leerlingen uit groep acht.
Samenvatting:
Deze these heeft als doel om te onderzoeken of elf jaar oude bassischool leerlingen kunnen profiteren van concept cartoons, ondersteund door self-explanation instructie. Er wordt onderzocht of de combinatie van deze twee instructie methoden nuttig kan zijn voor het leren begrijpen van data interpretatie en theorie revisie De concept cartoon-methode is een afbeelding waarin stripfiguren elk een andere opvatting hebben over een (natuurkundig) verschijnsel. De afwijkende opvattingen in de cartoons zijn zo ontworpen om een cognitief conflict te creëren, waarbij de participant verleid wordt om na te denken en eventueel een nieuwe theorie te vormen Echter, uit onderzoek blijkt dat deze methode het best kan worden ondersteund met prompts en het stellen van open vragen om effectief te zijn in het onderwijs (Stephenson & Warwick, 2002). Deze aanvulling kan worden gevonden in self-explanations. De constructieve aard, met aanmoediging tot integratie van nieuwe kennis en het continue verloop waarin het wordt uitgevoerd, kan een geschikte aanvulling zijn op de concept cartoon methode. Voor deze these is een natuurkundige taak ontworpen, waarin kinderen experimenteerden met verschillende ballen en moesten bepalen welke factoren (gewicht, grootte en kleur) van invloed waren op de valtijd. Deze taak is gebaseerd op twee principes: de algemene misvatting dat gewicht invloed heeft op de valtijd, en wetenschappelijke literatuur die beschrijft dat kinderen problemen ondervinden om resultaten te interpreteren die niet overeenkomen met hun verwachting. Deze studie onderzocht of de combinatie van concept cartoons en self-explanations effectief zijn om de kinderen te leren de resultaten correct te interpreteren en vervolgens een conclusie te trekken op basis van de resultaten in plaats van op hun oorspronkelijke verwachting. Drie condities werden gebruikt; een controleconditie (N = 14), een concept cartoon interventie (N = 15), en een concept cartoon met self-explanation instructie (N = 16). Drie variabelen werden onderzocht: cognitief conflict, data interpretatie, en theorie revisie. De resultaten lieten geen significante verschillen zien tussen de condities op het voorkomen van cognitieve conflicten of het reviseren van theorie. Ook was er geen significant effect van de interventies op correcte data interpretatie, behalve dat de combinatie van de concept cartoon en self-explanation er voor zorgden dat kinderen efficiënter gebruik maakten van de resultaten; ze hadden minder vergelijkingen nodig om tot een conclusie te komen, ongeacht de correctheid van deze conclusie.
Introduction
When we consider the contents of education of this century, it becomes clear that children are expected to familiarize themselves with scientific thinking at an early stage in education (American Association for the Advancement of Science, 1993; Greven & Letschert, 2006; Duschl, Schweingruber, Shouse, 2007). In the Netherlands, this is reflected in one of the attainment targets of primary education, which reads: “students learn to study materials and inquire about scientific phenomena such as light, sound, electricity, force, magnetism and temperature.” (Greven & Letschert, 2006). The highest level in secondary education in the Netherlands is called “VWO”, an abbreviation which roughly translates to „pre-university education‟. The highest aim for an elementary school-curriculum is to prepare children for this science-oriented education. Even though not every child will pursue a career in science, the thinking skills used in scientific inquiry can be beneficial for everyone (Ford & Forman, 2006; Metz, 2004; ONeill & Polman, 2004). Especially eight-grades (sixth-graders in American education) would benefit from closing the gap between elementary education and middle or high-school scientific-oriented education. Currently, this gap is believed to exist and according to Metz (2008), much larger than necessary. The current curriculum, where question, method and data analysis tools are given is still very remotely related to the practices in which knowledge is advanced. According to Metz, big ideas need to be central in the practices of the science classroom to stimulate prediction, observation, interpretation and explanation building. Her conclusion is that the elementary school classroom can and should more adequately reflect the robust goal structure of science as discovery and understanding. Recent research, documented by Gopnik (2012) has also made some challenging objections to current educational policy. According to her perspective, children‟s spontaneous exploratory and pretend play is designed to help them learn. In contrast to developing cognitive skills, early childhood should be more about socio-emotional development. Activities as encouragement of play, presenting anomalies and asking for explanations seem to prompt scientific thinking more effectively than direct instruction (Gopnik, 2012). She also states that policy-makers may acknowledge the importance of the socio-emotional aspect, but consistently seem to underestimate the intellectual capabilities of young children and preschoolers. Educational policy seems to focus on the development of cognitive skills, but play and social development have become shallow and underestimated. While aiming to cognitively develop children into competent and economically viable individuals, children‟s natural and play-like learning abilities should not be ignored. In its most ideal form,
elementary science education should involve the presentation of interesting anomalies in a playful way. This should be sufficient to activate the child‟s spontaneous and exploratory approach which they use to explain anomalies around them every day. In short, the gap between elementary and high school science education, as Metz (2008) argued, can be bridged by utilizing the children‟s spontaneous approach and molding this into a way of reasoning that is more in line with the scientific approach. To achieve this, science educators should first consider what children are already capable of, and with which aspects of scientific reasoning they have difficulties. Zimmerman (2007) has documented the many different aspects of scientific reasoning with which children have problems. She concludes that one of the major problems for children is to coordinate theory and evidence (Tschirgi, 1980; Schauble, 1988; Kuhn, 1993; Kuhn, Garcia-Mila, Zohar and Anderson, 1995; Zimmerman, 2007). When results do not match their hypothesis, children still have a natural tendency to draw conclusions based on their hypothesis. They also tend to ignore contradicting data or interpret it differently to make it fit better with their hypothesis (Kuhn et al, 1995). One can argue that confirmation bias explains this phenomenon, as Mynat, Doherty and Tweney (1977) concluded in earlier work. They found that when subjects design experiments, they try to confirm a hypothesis, instead of disconfirming it. Research by Schauble (1988) supports these findings: she found that children have difficulties discerning between their hypothesis and the results from an experiment, because they think the goal of an experiment is to produce an expected outcome instead of testing this expectation for truth. Whether problems with understanding the discrepancy between solid proof and a grounded (but not set-in-stone) hypothesis can be fully attributed to confirmation bias is questionable, and not the purpose of this study. The purpose of this study is to investigate if it is possible to support children in understanding that an hypothesis has an aspect of uncertainty, and that results from experiments are of a more certain nature. This could be achieved by developing an instructional intervention that assists children in discovering this for themselves, to help give them the insight that a systematic experiment will produce results, which should be used to reflect on a hypothesis to draw a „scientific‟ conclusion. This thesis argues for a novel method of instruction that utilizes a combination of two potentially powerful interventions; concept cartoons and self-explanation prompts.
scientific problem through a cartoon could, according to the studies described above, be successful in activating children‟s exploratory approach through the elicitation of cognitive conflict. If we consider this in light with the aforementioned problems with scientific reasoning, concept cartoons appear to be a suitable method to elicit cognitive conflict. However, concept cartoons alone will not be sufficient to stimulate conceptual change, as Stephenson (2002) emphasized, an efficient form of instruction should be included. A form of instruction that provides the support and open-ended questions that are necessary to stimulate discussion, solve the conflict and revise the theory subsequently. Ideally, an instructional intervention that connects with both the constructivist nature of the concept cartoons, and the constructive knowledge building that scientific reasoning entails.
The self-explanation effect in elementary science education
The self-explanation effect appears to have a long history in scientific literature. It can be argued that the roots of this line of research start with the discovery of children‟s self-directed speech by Piaget (1926). He stated this was an egocentric, non-directed „talk for self‟, in which the child verbalizes his or her thoughts in whatever form they occur. Vygotsky (1986) however, postulated that this self-directed form of speech had a much greater significance in the child‟s cognitive development. According to Vygotsky (1986), language helps children think about mental activities, behavior and to select courses of action. He viewed language as the foundation for all higher cognitive processes, including problem solving and abstract reasoning. He explained this „self-directed talk‟ as a way in which children guide themselves while solving a problem and called it „private speech‟ (Vygotsky, 1986). Most current studies about this form of self-directed speech support this view (Berk & Harris, 2003). One interesting finding is that when tasks become more challenging, or when children make errors or are confused, they use more private speech (Fernyhough & Fradley, 2005). Furthermore, evidence suggests that children, who use more self-guiding private speech, perform better on tasks than children who use less (Al-Namlah, Fernyhough & Meins, 2006; Berk & Spuhl, 1995; Fernyhough & Fradley, 2005; Winsler, Naglieri, & Manfra, 2006). Interestingly, this private speech tends to be internalized with age, changing into whispers and silent lip movements (Patrick & Abravanel, 2000; Winsler & Naglieri, 2003). It is possible that this phenomenon still exists among older children. If this is the case, it could very well be this
internalized speech as a feature that is elicited and strengthened by self-explaining. Therefore, private speech as a feature of self-explanation may be a valuable tool in supporting children with the scientific reasoning process. It is well documented in the cognitive-developmental literature that when children produce explanations while solving problems, they learn considerably more effective (Chi, Bassok, Reimann & Glaser, 1989; Russell & Kelley, 1991; Chi, De Leeuw, Chio & Lavancher, 1994; Renkl, Stark, Gruber & Mandl, 1995; Siegler, 2002; Calin-Jageman & Ratner, 2005; Williams & Lombrozo, 2009). This phenomenon is called the „self-explanation effect‟ by Chi et al (1989). They showed that when asking students to explain overtly what they did (and why) while solving a worked-out physics example, they proceduralize their declarative knowledge of physics and become better at solving similar problems. This conversion of declarative into procedural understanding is considered a critical aspect of learning and comprehension (Anderson, 1987). Placing this in the context of learning scientific discovery and reasoning, it is important that one learns to convert declarative knowledge on „how to solve a problem‟ into the procedural understanding of it. That is, when we give students scientific problems to solve, the ultimate goal should be that they learn to comprehend the hypothetical-deductive procedure of science. For this reason, the self-explanation effect could be effective because it seem to fit within the constructive context of scientific discovery. This association with the constructive context of science becomes more apparent in a deeper analysis of the self-explanation effect by Chi, de Leeuw, Chio and Lavancher (1994). They described three processing characteristics of self-explaining to prove its worth as an effective learning activity. The first characteristic is that self-explaining is a constructive activity. This statement is preceded by work of Simon (1979) who postulated that students learn both by being taught and by self-instruction. He based this on his finding that learning is a constructive process in which a student converts words and examples generated by a teacher or presented in a text into usable skills, such as problem solving skills. This process of conversion is essentially a form of constructive self-instruction (Simon, 1979). Research by Chi et al. (1994) also shows that declarative knowledge is constructed when self-explanation is used. However, as argued before, in the context of scientific reasoning one ought to be more interested in the construction of procedural knowledge of the process. Anderson (1987) argued that when learning occurs, the effortful process lies in the conversion of declarative knowledge into the procedural knowledge. This conversion process is arguably the key element in teaching children to use the scientific reasoning method. Taken together, it seems
importance of experimental results, and learn to discern between these results and their hypothesis. Subsequently, it could help in teaching children proper data-reading which should initiate theory revision about a scientific problem.
This study
This thesis aims to investigate whether sixth grade elementary students can benefit from concept cartoons with added self-explanations to learn to interpret data as a representation of „what really happened‟ as opposed to what they initially „belief that will happen‟. This coordination between the hypothesis-space and the experiment-space, as documented by Zimmerman (2007), appears to be problematic for children. The task constructed for this study is a simple physics experiment in which students have to figure out which of three factors influence the drop speed of small balls. The experiment is built upon two principles: the common misconception that weight has influence on falling time, and studies that show children have problems using data that disconfirms their initial hypothesis (Tschirgi, 1980; Schauble, 1988; Kuhn, 1993; Kuhn, Garcia-Mila, Zohar and Anderson, 1995; Zimmerman, 2007). The reason why this misconception was used, is to ensure that all participants had a common belief about something that is actually wrong and can be proven wrong by a simple experiment. The task will engage students in an experiment that will produce disconfirming evidence and is thus designed to elicit an internal conflict. This study investigated two aspects of scientific reasoning: data reading and theory revision. Three conditions were used to measure the effects of the concept cartoon and the self-explanation on data reading and theory revision. Two interventions; one with concept cartoons and one with concept cartoons plus a self-explanation prompt. Finally a control group was used for comparison. It was expected there would be differences between the three conditions on three variables; the occurrence of cognitive conflict, data reading, and theory revision. Cognitive conflict was expected to occur when the children would be confronted with disconfirming evidence. This internal conflict would be visible in a longer experiment time, more experiments performed, and more factors explored that were not initially hypothesized. In the control condition, we expected a minimal amount of time spent and small number of comparisons made. Because without the interventions, children would not be able to accept the disconfirming evidence, firmly holding onto their belief in the misconception Furthermore, we expected participants to mostly make comparisons with the initially
hypothesized factor, with minimal effort in investigating the factors that were left out of their hypothesis. This expectation is based on studies that show children have a tendency to confirm their beliefs instead of trying to disconfirm them (Mynat, Doherty and Tweney, 1977 ; Schauble, 1988). In the cartoon condition we expected more time spent and more total comparisons made by the participants, while they compare more factors that were not initially hypothesized. The concept cartoon would elicit a cognitive conflict for the children when they study the contradictory but apparently plausible ideas depicted in the cartoons (Schauble, 1988; Wittrock, 1994, Keogh & Naylor, 199 9 ). This could be visible in more thorough and time consuming investigation, and more with factors that were not hypothesized initially, as they could show interest in the new ideas presented in the cartoon. This was expected even more in the cartoon-SE condition, as the self-explaining would support elaboration on the cognitive conflict that occurs from the cartoon. This elaboration could increase understanding of how to resolve this conflict (Chi et al. (1994). Data reading was defined as the ability to draw a conclusion based on the results from the experiments performed with the data-cards. Our expectations were that in the control condition, participants would not be able to draw a conclusion based on the data, and would most likely draw conclusions that contained weight as a factor. According to the aforementioned scientific literature, children would have difficulty accepting the data (Mynat, Doherty & Tweney, 1977; Zimmerman, 2007). In the cartoon condition, it was expected that more participants would draw conclusions based on the data, with less conclusions based on weight (initially expected to be all children‟s misconception). The second cartoon depicted an example of how to use data to confirm the theories in the first cartoon, even without further prompted elaboration this could still inspire the children to pay more attention to the data. Hence, a small number of children could have gained the understanding that they had to use the data to draw conclusions. For the cartoon-SE condition, we expected participants to draw even more (or close to all) conclusions based on data and with even less based on weight. This is because the self-explaining is expected to elicit discussion and elaboration on the ideas depicted in the cartoons (Kuhn, 1972; Doise, Mugny & Perret-Clermont, 1975; VanLehn, 1988 , Chi et al, 1994). Especially after studying the second cartoon, we expect them to understand that they need the data to form a conclusion. Therefore, in this condition we also expect the conclusions to be more in line with the data that was used. The increased understanding of data reading is expected to lead to more efficient usage of it to draw conclusions.
The experiment consisted of a table setup on which a set of eight different balls was presented (Table 1). The balls were paired with stacks of data-cards. The data-cards were numbered (identical to the balls) and contained the descriptive properties of the corresponding balls. The backsides of these cards depicted the same information but with the (pre- calculated) falling time in seconds. To eliminate the balls‟ bouncy nature, a plastic bin filled with sand was used for the participants to drop the balls in.
Table 1: Properties of experimental balls
Object Diameter Mass Colour Time
Ball 1 4 .5 cm 5 gram Red 0 .50 sec Ball 2 4.5 cm 5 gram Blue 0.50 sec Ball 3 6.5 cm 5 gram Red 0.75 sec Ball 4 6.5 cm 5 gram Blue 0.75 sec Ball 5 4.5 cm 50 gram Red 0.50 sec Ball 6 4.5 cm 50 gram Blue 0.50 sec Ball 7 6.5 cm 50 gram Red 0.75 sec Ball 8 6.5 cm 50 gram Blue 0.75 sec
Concept cartoons. For the two experimental conditions, two different concept cartoons were used (Figure 1 and 2). Both cartoons contained the same four imaginary students. On the first concept cartoon, these students were depicted with a text-balloon in which an hypothesis was written about which factor(s) influence(s) the falling time (Table 2). On the second concept cartoon, these students were depicted with a text-balloon containing a conclusion related to their hypothesis, with a thought-balloon above depicting two data-cards corresponding to their conclusion (Table 3).
Figure 1: Concept cartoon A
Table 2: Concept cartoon A: Text balloons – Hypotheses
Person Hypothesis Explanation
Pietje I think color has influence on the falling time
Because dark paint consists of more pigments then light paint, blue balls must drop faster Johnny I think weight has influence on the falling time
Because heavy balls get pulled down more by gravity, so heavy balls must drop faster Karel
Joep
I think weight and color influence the falling time I think size has influence on the falling time
Because blue balls have more pigments, thus drop faster. Heavy balls exert more pressure so they drop faster. Because small balls float more easily, big balls drop faster.
Figure 3: Data-cards front and backside.
Equipment. For measurement purposes, a photo camera and an audio-recorder were used. The photo camera was used to record the number and contents of the comparisons between balls that the participants made with the data cards. The audio-recorder was used to record verbal utterances participants produced after the self-explanations were prompted. The purpose of these recordings was to validate if the prompts actually elicited self-explanations.
Procedure
To investigate whether children were able to draw a valid conclusion based on the presented data, a control condition was included. To investigate the effect of concept cartoons and self- explanation, two experimental conditions were used.
Control condition. In the control condition, participants were seated behind a table with the materials placed on top. The eight balls were presented with the data-cards, in the middle of the table, the information-card at the right side and the bin to drop the balls in on the left side. Participants received the instruction that all balls were different from each other and that they were allowed to inspect them. At this point, participants were asked which of the factors had influence on the falling time, with the specific instruction that there might be more than one. Participants were asked to elaborate on their answer, i.e. when they would say weight, they were asked if they thought a heavier ball would drop faster or slower than a light one. This part of the task will be referred to as the hypothesis-phase in the rest of this article. Next, in the experiment-phase, the participants received the instruction: “To see which ball drops faster, we can compare the falling times of the balls”, with the additional instruction that it is very hard to see which ball drops first and that because of that they could use the
data-cards. The first experiment was an example, guided by the experimenter. The participant received strict verbal instructions to select two balls that only differ in weight and were asked to first take the corresponding data-cards and place them on the layout. They were then instructed to drop the balls from one meter height at the same time, as precise as they were able to. They could repeat this three times maximum. When they had done this, they were instructed to flip the data-cards to read the exact falling times. At this point, the final instruction was to continue making similar comparisons until they thought they had enough information to form a conclusion. At any point, when they did not show any intent to make another comparison, we repeated this: “Do you think you know how it works now, can you make a conclusion?” Finally, in the conclusion-phase , the participants were asked which factors influenced falling time. Subsequently, they were asked to elaborate on whatever factors they concluded on, specifically: “Does a heavy ball drop faster than a light ball, or the other way around?”, or: “Does a small ball drop faster than a big ball?”, and at last: “How did you come up with this answer?” Cartoon condition. The first experimental condition was procedurally identical to the control condition, except for the presentation of the two concept cartoons. Concept cartoon A was presented at the start of the experiment-phase, with the specific instruction: “On this cartoon you see students who have thought about this as well. They all think differently about it. Take a good look at what they say.” The participant was allowed to study the cartoon for a maximum of 1 minute before the protocol was continued as described in the control condition procedure. They were then instructed that the falling time of the balls in the experiment was described on the backside of the data-cards, with the explanation that it was impossible to see that small difference in milliseconds without advanced equipment. The second concept cartoon (B) was also presented in the experiment-phase, right after this instruction. This was done in this particular order because we assumed this instruction alone would not be sufficient for the children to understand the link between the experiment and the data. To test for differences in effect between the conditions and the control group, the second cartoon in particular was expected to elicit this understanding. After this cartoon was presented, participants received the following specific instruction: “The students from the last cartoon have looked at the data-cards as well, and they now say the following about it. Take a good look.”. Again they were allowed to study the cartoon for a maximum of 1 minute. Hereafter, both the cartoons were removed from the table and the protocol continued as described in the control condition procedure.
(in seconds) to make comparisons, however, it may be informative to compare these to see if there is indeed a relation (and what kind) between time taken and number of comparisons. For example, a participant could be experimenting slow and thus take a long time. Both time taken and the number of comparisons made were compared across the conditions with analysis of variance. Time spent experimenting and the number of comparisons alone do not guarantee that participants were actually experiencing a conflict. They may have taken more time and made more comparisons but this could be for many reasons (just to have fun dropping the balls, the ball rolled off the table, the participant did not comprehend or was just slow, etc.). We needed information on why they took longer to experiment or why they made more comparisons before reaching a conclusion. This was measured by looking at which type of comparisons they made in relation to their initial hypothesis. For this purpose, photos of the compared data-cards for each participant were taken to score three variables: (1) number of colour- comparisons, (2) number of weight-comparisons and , (3) number of size-comparisons. We used these variables together with the initial hypotheses to score the number of comparisons made in line and those not in line with hypotheses. A minimal number of comparisons in line with initially hypothesized factors combined with a high number of comparisons not in line with hypotheses, should indicate that the participant has rejected their hypothesis and thus assumed to be in conflict about their theory. However, a high number of comparisons not in line, and a high number of comparisons in line with hypotheses could also be illustrative of a conflict. The participant may not believe the initial test results and thus looks for more confirmation before testing another theory. These scores were compared across the three conditions with a chi-square analysis, to see if any significant changes occurred. Data reading. To investigate if the experimental conditions had any effect on the participants ability to base their conclusions on data, the performance in correct data reading was measured. First, we asked the participants in the conclusion-phase how they came to their conclusion. When they addressed the data or data-cards in their answers, this was scored as (1) data reference, when they did not address the data or data-cards, this was scored as (0) no data reference. Chi-square analysis was used to test for any differences between the conditions. Secondly, we recorded the number of conclusions that contained weight as a factor and compared this across the conditions with a chi-square analysis. This was done to verify if they had read the data; if a conclusion was drawn based on weight it indicates they had not, as these data would show differences in weight had no influence.
To investigate if the answers from the participants were valid, we compared them with the information on the data-cards selected in the experiments. We then checked if any of the conclusions could actually have been drawn from the used data-cards. We counted how many comparisons they made containing the factors formulated in the conclusion. For instance if a conclusion was drawn that size was of influence, but the data-cards did not represent this factor, it was concluded that they did not use the data to formulate a conclusion. The number of compared pairs that contained the same factors as in the conclusion were then compared across the conditions with chi-square analysis. Theory revision. We first checked if the participants drew correct conclusions or not, this would indicate theory change, as all participants were assumed to initially have the weight misconception. A conclusion that described size as the factor of influence, with the explanation that smaller size is faster, was classified as a correct conclusion. Any other conclusions were classified as incorrect. The number of correct conclusions were compared across conditions with a chi-square analysis. To investigate theory revision regardless of drawing a correct conclusion, we compared the prior hypotheses about the effects of colour, weight and size with the final conclusions. We measured what kind of hypotheses and conclusions they formulated (colour, weight or size). We then compared these to see if concept change occurred. If the conclusion differed from the hypothesis, theory revision did occur. The number of participants that showed theory revision was then compared across the three conditions with a chi-square analysis.
Intellectual capabilities. After our initial data gathering, we considered the intellectual capabilities of our participants as they showed very good understanding of the task, even without interventions. Because of this, we have inquired afterwards about the high-school advice that these participants have received subsequently to an aptitude test (CITO, 2012). We checked how the different levels of advised future education (from low to high) were divided among the conditions, as shown in Figure 4. The two highest levels of education: HAVO and VWO are equally divided among the conditions (11, 10 and 12 respectively). However, compared to the experimental conditions almost twice as many participants in the control group received the highest grade of middle-school advice (9, 5 and 6 respectively).
