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A Preliminary Examination of a New Instructional Model for Conceptual Change.
GLENN DOLPHIN
Department of Science Teaching
Syracuse University
Syracuse, NY
grdolphi@syr.edu
Abstract: This paper is the result of a pilot study of the efficacy of a new instructional model for
conceptual change. The instructional model blends aspects from typically separate schools of
thought, including model based learning, writing to learn and drawing to learn, and features of
the nature of science. Science notebooks play a central role in documenting students’ creation of
knowledge and evolution of understanding. Instructors implemented this new instructional
approach in an introductory physical science course to teach the particulate nature of matter to
undergraduate preservice elementary teachers. The instructional model prompts students to elicit
their prior knowledge, through writing and diagramming, write testable questions, develop
predictions and procedures for inquiries, and conduct experiments. They collect and analyze
their own data and fashion claims based on gathered evidence. Through reflective activities,
small group and whole class discussions, students relate their claims back to their original mental
model to check for congruency, and describe how their original model was either supported or
refuted by their new information. Summative assessment data based on open-ended exam
questions and an essay assignment provide some evidence of student metacognitive processing
and conceptual content change. Many students recognized that their initial understanding of
matter was very general and did not incorporate descriptions of particles. Some students even
recognized that the very act of writing the essay helped them to deepen their understanding and
build their mental model. The paper outlines this integrated instructional model, describes some
of the evidence supporting the claim of deepening understanding, discusses some implications
for teaching the nature of science, and proposes areas of future possible research.
1.0
Introduction
The last 30 years has seen a shift in science education in our understanding of how
students learn. Students in science classrooms are no longer seen as “empty vessels” waiting to
be filled, or “blank slates” waiting to be written on. It has become increasingly obvious that
students come to school, even in the earliest years, with an understanding of how the world
works based on their own observations and reasoning abilities. These understandings or
conceptions come in various levels of completeness and accuracy compared to current scientific
thought. Researchers in science education have learned that these “naïve,” “alternative,” or
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“mis-” conceptions are not only tenacious, but will fundamentally impact what and how the
student will learn. In this light, researchers have created and tested different instructional
models, for instance, the 5-E cycle (Bybee, Taylor, Gardner, Van Scotter, Bloom, Moran et al.,
2006), model co-construction and evolution (Khan, 2008), Gagné’s nine events of instruction
(Gagné, Briggs & Wager, 1992), and mediated modeling (Halloun, 2007, 2004).
However, these methods of instruction are founded on what Bereiter (2002) calls a folk
theory of mind. This theory considers the mind a container and knowledge something that is put
into and/or modified within the container. He goes on to claim that this theory of mind is losing
its usefulness in a society where knowledge creation is becoming more important. “A viable
theory of mind for 21st century education, it seems to me, must be able to negotiate effectively
between individual learning on the one hand and knowledge conceived of as a product or as a
cultural good on the other” (p. 20). He sees the container metaphor as being adequate for
explaining how learners acquire knowledge but insufficient to explain what that knowledge can
be used for once it is there.
Sfard (1998) also has misgivings for this model of learning - what she refers to as the
acquisition metaphor. This metaphor also posits the mind as a vessel for knowledge acquisition.
She points out that according to the acquisition metaphor, the learner must rely on previous
knowledge in order to acquire new knowledge. This brings up the paradox: How can the learner
rely on the previous knowledge of something that (s)he does not already know? In contrast to
the acquisition metaphor, Sfard describes a second model of learning - the participation
metaphor. Here, knowledge is not separate and objectified but part of the interaction between
the learner and his or her environment. Instead of gathering information as one would
possessions, the participation metaphor explains learning as happening during discourse and
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practice situated within the context of a community. Bereiter (2002) acknowledges that all
human behavior is situated, however he also points out that school mathematics, for example “is
not knowledge that is embedded in a community of practice but rather is knowledge there for the
taking, by anyone who has access to it and who can make something of it” (p.61). Due to the
differences between each metaphor in how they define knowledge, learning, and understanding,
they each prescribe different strategies of instruction. The acquisition metaphor advocates such
strategies as activating prior knowledge, advance organizers (concept maps, outlines, Venn
diagrams, etc) mental modeling and diagramming. The participation metaphor advocates
learning communities and cooperative/collaborative groups, rehearsal, and cognitive
apprenticeships and coaching.
Even though many researchers find themselves defending one or the other metaphor as
being the closest to explaining how learning actually takes place (see Anderson, Redder, &
Simon, 1996; Anderson, Redder, & Simon, 1997; Greeno, 1997 for an example of this), Sfard
(1998) states that not only are both metaphors useful, but they should be used together so that
one can fill in the gaps the other one leaves. She goes on to state that the two metaphors are not
mutually exclusive but incommensurable. “Thus, for instance, today’s mathematicians are able
to live with Euclidean and non-Euclidean geometries without privileging any one of them,
whereas contemporary physicists admit a mixture of ostensibly contradictory approaches to
subatomic phenomena, sanctioning this decision with Bohr’s famous principle of
complementarity” (p. 11).
2.0
Toward a New “Inclusive” Theoretical Framework
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Paavola and Hakkarainen (2005) acknowledge the contributions of the theories
supporting the acquisition and participation metaphors. However, they also point out a
deficiency in both. Where the acquisition metaphor focuses on the delivery of knowledge to the
mind and the participation metaphor focuses on the transference of knowledge from person to
person, neither one makes accommodation for the generation of new knowledge. Paavola et al.
(2004) cite three knowledge creation models, Nonaka and Takeuchi’s (1995) model of
knowledge creation, Engeström’s (1999) model of expansive learning, and Bereiter’s (2002)
model of knowledge building, to draw attention to the significant gap in the acquisition and
participation metaphors; neither adequately address the creation of new knowledge. With the
motivation to emphasize the importance of the acquisition and participation metaphors, and fill
this gap, Paavola et al. (2004) propose a third metaphor of learning - the knowledge creation
metaphor. They describe it as model that “conceptualize[s] learning and knowledge
advancement as collaborative processes for developing shared objects of activity. Learning is
not conceptualized as occurring in the individuals’ minds, or through processes of social
practices. Learning is understood as a collaborative effort directed toward developing some
mediated artifacts, broadly defined as including knowledge, ideas, practices and material or
conceptual artifacts” (pp. 569-570).
Within the context of the knowledge creation metaphor, Paavola and Hakkarainen (2005)
call for a change in the educational system. They argue that schools should become communities
where teachers and students alike have rich experiences in knowledge building. They emphasize
a model of progressive inquiry where “explanation seeking processes and collaborative and
social aspects of learning are emphasized. The model depicts a deepening question-explanation
process where students collaboratively create context, set up research questions, construct
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working theories and critically evaluate the process” (p. 549). The knowledge creation metaphor
differs from the acquisition metaphor in that it does not focus on the transfer of knowledge but
rather the creation of new knowledge. However, the individual is still important as the bringer of
knowledge and intuition that can be used to solve problems posed to the group. Although the
work of knowledge creation does happen within a social context, as it does in the participation
metaphor, it differs from that model because the focus is not on the dynamics of group
interaction but on the product of that interaction (Paavola & Hakkarainen, 2005). They
encourage the use of all the metaphors to capture the learning process best.
3.0
The Unifying Instructional Model
The instructional model proposed in this paper is situated within the framework of the
knowledge creation metaphor (Paavola & Hakkarainen, 2005; Paavola et al., 2004). Within this
framework, “explanation seeking processes, and collaborative and social aspects of learning are
emphasized…the most promising tools are ones that guide the participants themselves to engage
in extensive working to produce knowledge through writing and visualization.” (p. 549). Paavola
and Hakkarainen (2005) also encourage students to make notes, pose questions, explain their
own understandings and finally present knowledge gains thereby “organizing the learning
community’s activity around shared objects of inquiry” (p. 550). Essentially, the knowledge
creation metaphor incorporates the cognitive sciences with socio-constructivist epistemologies
and then adds a new facet. This facet emphasizes the importance of mediating artifacts.
Mediating artifacts can be concepts, theories, activities or practices. Instruction is successful
when students are working in small groups, constructing knowledge in the form of these
artifacts, individually and as a group, and revisiting previous understandings in light of new
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observations. Bereiter (2002) encourages telling students that they are not developing a
relationship with the actual phenomenon but rather with their understanding of the phenomenon
being investigated. Paavola and Hakkarainen (2005) argue that although young children may not
be in a position to create knowledge in a historic sense, they should be creating knowledge
relative to their original position.
The general progression of the new instructional cycle has been modeled after the
“levels of target concepts,” as described by Rae-Remirez (2008). Within this structure, the
instructor chooses an “optimum integrated target concept” (p. 49). This can come from learning
standards (AAAS, 1993; NRC, 1996) and is a major theme or “big idea” to be taught. For
instance, standard 4D “Structure of Matter” (AAAS, 1993) would be an example of such an
optimum integrated target concept. The instructor parses this major theme out into several
different target models (target model 1 + target model 2 + target model 3 = optimum integrated
target concept). This would correspond to “Atoms and Molecules,” “Conservation of Matter,”
“States of Matter,” and “Chemical Reactions” (AAAS, 2001). The instructor then plans several
instructional cycles within the context of each target model to lead students though a gradual
enrichment or sophistication of intermediate models until the appropriate target model has been
built (intermediate model 1a → intermediate model 1b → intermediate model 1c → target model
1). Khan (2008) includes the following indicators for recognizing an enriched intermediate
model.
Indicators that a student’s expressed model appears to be more enriched include:
(a) an addition of new variables to the model, (b) an addition of modifiers to
relationships within the model, (c) use of relationships within the model to
explain novel lab findings, (d) change of drawings of molecular structures, and (e)
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ability to make predictions and offer explanations that students were not able to
do…prior to the learning episode. (p. 60-61)
Each cycle (Figure 1) within the progression begins with the instructor eliciting students’
prior knowledge through a demonstration or questions about the phenomenon to be studied. The
students express their mental model either through writing or drawing diagrams with
spatial/static and causal/dynamic aspects. They do this with an emphasis on addressing the
demonstration or answering the questions. The instructor then provokes conceptual
dissatisfaction or cognitive dissonance by performing a discrepant event or asking one or more
discrepant questions (Rea-Remirez & Núñez-Oviedo, 2008). The instructor directs the class into
one of two possible paths. Path I revolves around a large group discussion about the concept
where competing student ideas can be expressed, rationalized and argued (Núñez-Oviedo &
Clement, 2008; Núñez-Oviedo, Clement, & Rea-Remirez, 2008). Utilizing multiple
representations of the concept during whole class discussion provides information for helping
students modify their mental model (Boulter & Buckley, 2000) and create meaning for the whole
group. Results of this discussion become the subject of a reflective writing assignment, or
conceptual artifact of Bereiter (2002), where students record the effect of the discussion on their
mental model and compare and contrast their new model with the model they held previously.
The emphasis on this and all writing is one of the future utility of this knowledge and not just for
assessment.
From cognitive dissonance, path II involves the instructor giving boundaries or
parameters for exploration into the concept by having students work on an inquiry activity.
Boundaries could be anything from the set of substances to be used in an investigation of
chemical reactions to a discussion of the concept being explored. It is a way to scaffold the
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investigations to support the students’ inquiry and prevent investigations from becoming a
practice of “trial and error.” Students write testable questions and develop and defend
predictions and procedures, based on their mental model. They conduct experiments, collect and
analyze data, and fashion claims based on gathered evidence. Through reflective activities and
small group and whole class discussions, students relate their claims back to their original mental
model to check for congruency, and describe how their original model was either supported or
refuted by their new information. Students keep all of their information in a science notebook,
an artifact of the knowledge creation process, to reference their prior understandings for
comparison to newer ones and for refining their mental model. The instructor initiates another
cycle with a new discrepant event to push students to further refine their mental model.
4.0 Review of Instructional Strategies
The instructional cycle proposed here combines many of the strategies traditionally
separated between the two metaphors of learning. This section lists the strategies utilized within
the instructional cycle and discusses its research based role in enhancing student understanding
and knowledge creation. The strategies appear below in a certain sequence. This is merely an
artifact of the linear nature of the writing process. There is really no specific order for the
strategies as will be illustrated in the accompanying figures. The prime objective is to focus on
“the richness of what there is to be learned. Major theories have great depth and wide
implications. Coming to understand a living theory means establishing a many-faceted
relationship and one that will keep developing as one’s experience grows and the theory itself
evolves” (Bereiter, 2002, p 119).
4.1 Accessing prior knowledge
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The instructional cycle, shown in Figure 2, begins with eliciting students’ prior
knowledge and then creating dissatisfaction within the students concerning that prior
understanding. The importance of prior knowledge within the scope of learning has been
emphasized since the 1950’s within the framework of cognitive information processing and later
in the 1970’s with meaningful learning and schema theory (Driscoll, 2005). Appleton (1997)
found the importance of activating students’ prior knowledge and eliciting conceptual
dissatisfaction through the use of teacher derived discrepant events. By studying middle school
science students (11-13 years of age) through videotaped lessons, interviews, and field
observations, Appleton (1997) gained insight into the cognitive response of research participants
to constructivist teaching methodologies. His model of conceptual development begins with the
notion that “[t]he learner brings to the learning situation all previous experiences and
feelings…which are used to interpret and make sense of any new encounter” (p. 308). Taber
(2003) describes a similar notion from his study of first and second year college chemistry
students. After conducting student interviews and analyzing student writings and diagramming
activities, he posits that college students’ learning about chemical bonding “was found to be
strongly channeled by prior learning” (p. 751). Taber (2003) emphasizes the importance of
uncovering students’ prior understandings, identifying possible misconceptions, and informing
teachers of the learning process. With this information, teachers may adapt instruction to
facilitate the conceptual change process. In their study of eighth grade students in a physical
science class, Smith, Maclin, Grosslight, and Davis (1997) found that the beliefs students come
to class with profoundly affect what they learn during instruction. In their study, they found that
students did not come to have an accurate understanding of density until they first understood
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that matter would continue to exist when broken up, even if the pieces were too small to be
observed.
In a study of introductory college physics students’ learning about special relativity,
Posner, Strike, Hewson, and Gertzog (1982) found that students did not accept a new concept
unless there was a need for the new concept. Their interpretation of the interviews of the physics
students was that unless there was dissatisfaction with their current understandings of a concept,
students were not likely to exchange their explanation with an explanation that more closely
parallels current scientific understanding. This “dissatisfaction” can be brought about through
the use of an anomaly, an experience that cannot be reconciled with the students’ current
understanding (Posner et al., 1982). Only in the face of a need to make sense of an occurrence
were students open to alternative conceptions. Posner et al. (1982) also note that the alternative
explanation needs to be understandable, plausible, and fruitful. Subsequent critiques of this
model (Pintrich, Marx, & Boyle, 1993; Strike & Posner, 1992) broaden the model to also include
students’ attitude, motivation and self-efficacy as crucial determinants to conceptual change.
4.2 Diagramming
Diagramming is an important aspect at various stages along the instructional cycle
(Figure 3). It can be utilized for expressing both prior and newly acquired knowledge, making
predictions, and supporting claims. In her study of 40 fifth grade students, Gobert (2000; 2005)
had students read text about plate tectonics and had them draw diagrams to represent what they
had just read. Students then made inferences about related geologic phenomena based on their
diagrams. It is the use of the diagram, or conceptual artifact, as a tool to further one’s knowledge
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that reflects the the knowledge creation metaphor. Gobert’s (2000) results highlight the efficacy
of having students draw diagrams, as opposed to being given diagrams of a concept.
Results from these studies suggest that young students can construct rich mental
models of complex causal and dynamic systems, which they can then use to make
inferences. These data also suggest that developing rich integrated causal models
may be facilitated when models are constructed by the learner beginning with the
static components first followed by increasingly complex models involving causal
and dynamic information. (p. 965, emphasis mine)
Gobert and Clement (1999) and Gobert (2005) describe the strength of student-generated models
in developing strong conceptual understanding. Fifth grade students read passages describing
plate tectonics. One group answered questions about the text, another group intermittently wrote
summaries of the text and then answered questions about the text, and a third group
intermittently drew diagrams summarizing the reading, and then answered questions. The
researchers found that though the written summaries for the text were more detailed than the
student generated diagrams, the students who did the diagramming tended to show better
understanding for spatial, causal and dynamic information than the group who wrote summaries
and the group who did nothing after the reading.
4.3 Writing
With the emphasis on literacy becoming more potent, writing in science is also becoming
more common. Different types of writing activities can occur along the instructional cycle as
demonstrated in Figure 4. Keys (2000) and Keys et al. (1999) experimented with a Science
Writing Heuristic (SWH) to see if purposeful writing during laboratory activities would help
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eighth grade students build new knowledge. The SWH consists of a template of teacher
designed activities and a template for student thinking (Keys et al., 1999). The teacher designed
writing activities include concept mapping, writing about activities that include students’
personal meanings, data interpretation and comparison with others, individual reflections, and
writings for presentation to the whole class. The student template consists of a number of
guiding questions to facilitate understanding throughout the activity, such as “What did I do?
What did I see? What can I claim? How do I know? How do my ideas compare with other
ideas? How have my ideas changed?” (p. 1069). Keys et al. (1999) found that the use of SWH
embedded within laboratory activities encouraged students to construct knowledge and generate
meaning in the content domain and to a modest effect in the nature of science. Using the same
SWH in a different class, Keys (2000) found that some students utilized writing specifically to
reflect on the science content, solve problems, and generate new knowledge.
Klein (2004) outlines four different factors that led to higher learning outcomes from a
group of undergraduate non-science majors writing about a scientific activity in which they
participated. The first factor was setting content goals. Students were told explicitly that the
writing they were doing was for their own learning. The second factor was the student use of
experimental results as a resource for idea and text generation. This illustrates the importance of
utilizing a science notebook. The third factor was the use of comparison writing while
describing the activity. Lastly, he describes student difficulty in writing as being an indicator of
knowledge construction. The most common use for writing assignments has been as a form of
assessment. However, as noted above, it is important to emphasize that the writing is not the end
of, but merely a part of the learning process and what the students write should be used in
furthering their understanding.
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4.4 Multiple Modes of External Representations
“A model in science is a representation of a phenomenon initially produced … as a
simplification of the phenomenon to be used in enquires” (Gilbert, Boulter, & Elmer, 2000, p.
11). However, many students see models (see Figure 5) as “replicas” of reality and see their
purpose as mainly the transference of knowledge about the phenomenon (target) rather than tools
for inference or prediction (Grosslight, Unger, Jay, & Smith, 1991). Boulter and Buckley (2000)
outline and define the different modes and attributes of representations that can be used in
instruction. Utilizing a variety of representations for a single concept can help students develop
a more robust understanding of the target phenomenon (Boulter & Buckley, 2000; Grosslight et
al., 1991). One caveat to this claim is that the purpose for each model be made explicit to
students to avert possible confusion. For instance, Flodin (2009) found that several different
models used for the target, “gene,” occurred within the same textbook – “gene as trait, an
information structure, an actor in the cell, a regulator in embryonic development, or as marker
for evolutionary change” (p. 91) – but without explicitly stating these differences or the
overlapping and/or related functions. This can cause a great deal of confusion for the student.
Different strategies for model use in science class have been shown to be effective.
Students’ explicit revision of models and model use for solving problems has also been shown to
increase their constructive epistemologies (Grosslight et al., 1991). In their study of eighth grade
students, Ardac and Akaygun (2005) found that the use of dynamic models representing
chemical changes at the molecular level were more effective than static models of the same
targets for facilitating student understanding of that phenomenon. Else, Clement, and RaeRemirez (2008) outline several strategies for effective model use in the classroom. These
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strategies include discussing student understandings in light of the model and using drawings and
diagrams to map out the relationship between model and target. They also emphasize the
importance of highlighting that models are representations with a specific purpose, and that
certain aspects of the target are represented, and certain aspects of the target are not represented.
4.5 Socially Mediated Activities
Much of the learning happening in classrooms is social in nature (see Figure 6).
“Learning Science involves young people entering into a different way of thinking about and
explaining the natural world; becoming socialized to a greater or lesser extent into the practices
of the scientific community with its particular purposes, ways of seeing, and ways of supporting
its knowledge claims” (Driver, Asoko, Leach, Mortimer, & Scott, 1994). There is learning that
happens among students in small and large group discussions. There is learning that happens
during interactions between teacher and student. Nunez-Oviedo and Clement (2008) describe a
“competition strategy” for learning in which students present their own ideas in discussion.
These ideas may be contradictory to each other and this contradiction fosters cognitive
dissonance in the students as they try to figure out which idea best suits observations. During
this process, the group created meaning through different modes of model evolution, including
dropping criticized models out of discussion (disconfirmation mode), dropping, adding or
changing aspects of particular models (modification mode), creating new models (generation
mode), and agreeing on a model that fits the parameters best (confirmation mode).
Piaxão, Caldo, Ferreira, Alves, and Morais (2004) demonstrated the efficacy of group
discussion and reflection when teaching plate tectonics to seventh grade students. Students were
given prompts in terms of a question or a hypothetical situation. They had to then determine a
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response and discuss reasons for their response within groups or the whole class. The discussion
technique of Piaxão et al. (2004) revolves around utilizing historical aspects of the development
of the theory of plate tectonics. As such, they found that the strategy not only demonstrated how
scientists (and students) learn, but also how scientific knowledge is created by a community of
scientists (and a community of students).
The conversations between teacher and student can be just as important in the learning
process. Within their analysis of teacher talk, Ryder and Leach (2006) found that if teachers
employed certain strategies during their classroom talk, they would have a positive impact on
students’ epistemologies of science. These strategies included making appropriate statements
about the epistemology of science, linking scientific epistemology with science content, and
stating and justifying learning aims. They describe the following strategies as having a positive
impact on students’ epistemologies of science: “(a) asking for students’ ideas, (b) highlighting
students’ ideas during whole class discussions, (c) asking students to justify their ideas, (d)
challenging students’ ideas, (e) evaluating students’ ideas, and (f) introducing known student
misconceptions” (p. 305). Many of these same strategies were utilized successfully to promote
the evolution of students’ mental models in a biology class (Núñez-Oviedo, Clement, & ReaRemirez, 2008). Their qualitative data of teacher-student(s) interaction demonstrated how the
teacher facilitated the evolution of the students’ mental models of concepts such as “valves
inside veins,” and diffusion in a biology class.
Syh-Jong (2007) studied how students in a teacher preparation program taking a physical
science program were able to construct knowledge within the content domain as a result of
writing and talking in a small group format. The students broke into groups and performed the
activities within the topic and discussed and wrote about their experiences within a journal.
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Once all of the activities in the topic had been accomplished and discussed, the group made a
presentation of findings to the rest of the class. If there were discrepancies within the class about
findings, discussions ensued to rectify them. At the end of the course Syh-Jong noted that (a)
The majority of students felt the teaching/learning experience to be effective. (b) Students coconstructed knowledge from working, speaking and writing in small groups. (c) Speaking and
writing in small groups was responsible for their explicit understanding of knowledge within the
content domain. (d) Small group, collaborative work encouraged the students to become active
learners within the course. What he found was that most students felt that this teaching/learning
environment was conducive to good learning. He also noted that students in the class
transitioned from passive students to active, full participants within the small group environment.
He posits that “speaking and writing in a collaborative group mutually stimulated students in
constructing knowledge” (p. 78). In other words, writing helped students organize their thoughts
for speaking to the rest of their group, while speaking helped them make explicit what was
implicit in their writing.
4.6 Metacognitive Activities
“Metacognition refers to one’s awareness of thinking and the self regulatory behavior that
accompanies this awareness” (Driscoll, 2005, p. 107). Though activities that incorporate
metacognition overlap and incorporate many of the previously described strategies, it is treated
as a separate entity here to emphasize its importance (see Figure 7). In a study about the mental
models undergraduate chemistry students hold regarding the structure of matter, FloresCamacho, Gallegos-Cázares, Garritz, and García-Franco (2007) found that the students could
hold multiple mental models of matter at any one time. They also found that the multiple models
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held by any one student could be incommensurable with each other, meaning that parts of each
model may utilize the same term, however that term is assigned a different and incompatible
meaning for each model making the models incomparable. They found this to have an impact on
student learning. Implications from this study suggest the importance of making students aware
of their different mental models and the context in which they are used. Students can analyze
their models for limitations with the intent to get them to discard the less effective ones in favor
of the ones better aligned with current scientific thought (Camacho, et al., 2007).
Inquiry skills and scientific ability in biology were shown to be positively influenced by
metacognitive activities in a group of tenth grade biology students (Zion, Michalsky, &
Mevarech, 2005). Activities included posing problems to students and then having them write
about their problem solving thinking. Students described their goals and strategies for solving the
problem as well as their rationales. They assessed their own activity during the process,
describing what difficulties they encountered. Zion et al. (2005) also found that students
communicating in text through a computer interface with students from another school
(asynchronous learning network) also had higher performance scores than those speaking face to
face in the same class about the same situations. This supports the notion that writing has a
positive effect in the learning process as well (see 4.3 above).
Two important aspects of learning for understanding is the ability of the learner to take
what has been learned and be able to transfer it to new situations and to utilize the learned
material for a long time (not just until the test). Georghiades (2000; 2004) found that
metacognitive instruction (discussing/reflecting, keeping diaries, concept mapping, and
analyzing models) embedded within the fifth grade science curriculum increased both of these
aspects significantly against those who received the same content material but without the
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metacognitive activities. Interestingly, Georghiades (2000) found that students who received
metacognitive instruction showed only slightly better learning than the control group
immediately following instruction, but showed dramatically better retention of material when
tested eight months later.
5.0 Pilot Study Implementation
I implemented the unifying instructional model along with the instructor of record for a
course during the spring semester of 2009. The instruction took place in the two sections of an
introductory physical science class for preservice elementary teachers in an inclusive elementary
education program at a large Research I university in the northeastern United States. There were
80 participants, 76 females and 4 males. Forty of the students were in one of the sections and
taught by the instructor of record of the course. I taught the other 40 students in a separate
section. Most students were first-year students and this was the second semester of a twosemester sequence in science and became participants by virtue of their being in the course. Our
common planning helped ensure that we each taught both sections similarly. Enhancing these
preservice teachers’ understanding of scientific concepts has far reaching implications. Science
instruction has been shown to be more effective when teachers have a firm understanding of the
content they are teaching. Higher quality elementary science instruction has also been shown to
have a positive effect on students’ performance in science through high school.
On the first day of the class, I introduced the students to several ideas. These included
the use of models in science, the idea that they construct their own understandings of reality, and
that their understanding is called their mental model. We discussed the use of such models to
either describe a phenomenon or explain a phenomenon. I then had students record their mental
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model of the nature of matter. We continued to incorporate activities which would demonstrate
aspects of matter’s particulate nature for the next several weeks. Bereiter (2002) stated that “[i]t
begins getting students on sufficiently intimate terms with the object to be understood that they
can ask why questions with some meat” (p. 126, his italics). The object, or conceptual artifact, to
be understood is the kinetic molecular theory. To do this, we started with an activity where
students placed a couple of drops of vanilla extract into a balloon, inflated it, tied it off and then
made observations of the balloon-vanilla-breath system. During the activity, the alcohol base of
extract evaporated, permeated the latex, and students smelled the vanilla on the outside of the
balloon. Students then developed a preliminary model (a diagram with written explanation) to
explain their observations. Over the next few classes, and through similar activities and
investigations, we introduced students to the properties and phases of matter. Students utilized
and modified their models as a foundation for explaining their subsequent experiences. Students
kept a science notebook where they collectively or independently recorded predictions,
procedures, observations, and finally made evidence based claims. After completion of each
activity, we directed students to revisit their mental model of matter to test it for congruency with
what they had just observed. We also conducted small and whole group discussions about
important aspects of the activities and demonstrations. We encouraged students to pose their
questions and posit possible answers with rationales based on their working models. We had
them record these reflections in their science notebook as well. There were very few truly
experimental activities. We had preset many of the variables and students made predictions
about reactions and justified those reactions based on their mental model.
At the end of the series of investigations, we assessed students on a slide presentation that
each small group made to the whole class. The “mediated artifact” consisted of a claim that the
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group developed as a result of activities and the evidence to support their claim came from their
observations during the activities. We collected students’ science notebooks, and using a rubric,
checked them for completeness. We also assigned an essay asking students to make three claims
about the particulate nature of matter from their mental model and to support each claim with
evidence from the activities. Students also wrote a metacognitive piece describing the impact of
the class activities and discussion on their mental model of matter. Finally, we gave students a
final exam composed of open ended questions probing their understandings of various aspects of
the nature of matter.
The data we gathered came from science notebook entries, student essays describing their
understanding of structure of matter as they compared and contrasted that new understanding
with the understanding they started the class with. We also used responses to questions on the
midterm exam and their class presentations - each consisting of a claim about the structure of
matter with evidence. We looked for an evolution and utilization of students’ models, which
were recorded and revised in their science notebooks, along the progression of activities.
5.1 Preliminary Findings
I examined students’ science notebooks, essays and exams and allowed general themes in
the data to emerge. Initial patterns in the data showed that students’ initial mental models were
very simplistic and general. Students made statements such as, “Matter is everywhere,” Matter
is everything that we see,” “Matter comes in three phases,” and “Matter exists as a solid, liquid,
or gas.” There was minimal mention or indication in any of the responses that matter was made
of tiny particles and that the behavior of these particles determined the behavior of the matter
they made up.
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The essay assignment and final exam drew these responses:

I know that water, specifically, has a high capillary action because water particles stick to
each other and other substances…

…liquid takes on the shape of its container because the bonds between the molecules are
not strong enough to hold it in one specific shape.

I believe that when she pulls the syringe (of a confined gas) back, to 20ml the
temperature should decrease because of the lower frequency of particle collisions.
As can be seen from the examples, student ideas about matter show a definite increase toward
sophistication. Instead of describing matter only in terms of it phases or by its ubiquitous nature,
students have included references to the particle nature of matter. They also go on to describe
that these particles interact with each other; they stick together or they collide against one
another.
Some explanations also utilized student-derived analogies as part of their mental models.
Two examples that we noted were:

A balloon served as a good example to describe the nature of a solid’s wholeness (or
hole-ness): its material is composed by a pattern of overlapping threads, and though
together they form a ‘solid’ balloon, among those woven rubber threads are tiny spaces
which allowed the scent to travel through (my emphasis).

Another way to think of matter as being mostly empty space is by comparing it to a chain
link fence. A chain link fence is mostly empty space and human hands can be put
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through it, however the ‘bonds’ of the fence are strong and it is hard to break, this is
similar to the strength and tightness of matter.
Since the analogies illustrated in the quotes above are not examples of analogies used in
classroom discussion, this process of model construction must be a case of the students building
this new knowledge into their personal prior knowledge framework, indicating more meaningful
learning.
5.2 Student Metacognition
Within their essays, we asked students to conclude by making and then supporting the
claim that their mental model of matter had been impacted in some way due to instruction. The
following are some quotes from different essays:

I tried to recollect the images and the ideas that I remembered from high school science
classes about properties and behaviors of matter, but all I could remember were simple
ideas about the separate three phases. I had no complex beliefs about matter and didn’t
make any statements about how the three stages of matter could relate to one another
(student emphasis).

My mental model of matter began very general and has expanded through
experimentation and discussion with peers.

Just by writing this paper I realized how much more information I know about the nature
of matter now than I did on the first day.

The process of writing this essay has further developed my model as well, because it
forced me to analyze my claims and make them general, so that they are true not to just
one specific experiment, but matter as a whole.
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
My mental model has greatly improved, coming from not even knowing what one was, to
now formulating hypotheses from what I already possess in my mental model. (emphasis
mine)

Through this learning experience I discovered that I have a mental model that can be
altered and added onto.
By having students create a written record of what they thought about matter, prior to instruction,
they had a reference point from which to gauge their progress through the course of instruction.
Not only did some students become aware that they had a mental model, but that they could
impact that mental model by relating their experiences to it and looking for coherence between
model and observation. Some even gained insight into the fact that their mental model can be
used to make hypotheses and predictions about phenomena.
5.3 Other Observations
Another observation that we made as the course of instruction progressed was student
inability to tell the difference between claims and evidence. Often, claims made by students
were a restatement of their observations but without the data presented. For instance, students
explored Boyle’s law where an amount of gas was placed into a syringe and hooked up to a
pressure sensor so students could record pressure changes within the syringe resulting from
changing the volume of the gas by pushing in or pulling out the plunger of the syringe. At the
conclusion of the activity, many students made the claim that as the volume of a confined gas
decreased, the pressure increased. They supported this claim with evidence which said the exact
same thing, only with their empirical data. They did not seem to be able to connect this activity
with any others that demonstrated how matter takes up space, or that the pressure is caused by
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the force exerted by colliding particles. In their essays, although few were able to make claims
about matter which they supported across a spectrum of activities, most made claims of a very
limited nature, dealing with results of only one activity.
This inability to make claims with broader implications is most likely related to a second
limitation of their claim generation; most of the claims they made were strictly descriptive in
nature. They described the relationship between different variables, namely pressure and volume
of a gas, temperature and phase, and the reactions created when certain substance are mixed
together. There were very few claims that were explanatory in nature. These would be claims
revolving around the particulate nature of matter. In both classes, we discussed the idea of
particles making up matter and showed various modes representing this concept. When
expressed, models which utilized these few examples were isolated to the context in which they
were introduced. There did not seem to be much carryover from one activity to the next.
Another observation we made was the gradual emergence of certain misconceptions
during the evolution of their mental models. One such misconception was their
anthropomorphism of matter. After studying the behaviors of matter under different conditions,
student descriptions of that behavior contained allusions to human behavior. Examples of this
are demonstrated in the following quotes: “The vanilla traveled through the pores in the balloon
to outside it, trying to equalize the concentration,” “The gas has the ability to travel through a
solid,” and “Matter is capable of changing its form due to its surrounding environment.” Here,
students have tried to give inanimate material decidedly human qualities as desire and capability
to perform an action.
Another interesting misconception developed as a direct result of instruction. We
presented students with the idea of a chemical reaction being one where two or more substances,
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when brought together, can react and create new substances. They explored a few examples of
this and surmised that indications of such a chemical change can be a color change, the
production of a gas, and a temperature change. A final demonstration involving phase changes
utilized dry ice placed in water which was red from the added phenol red indicator. Of course
the students observed violent bubbling from the sublimation of the dry ice. Carbon dioxide
dissolving into the water turned the indicator from red to yellow, as the pH turned from neutral to
acidic. Condensation began to form on the outside of the jar of water as energy was used to turn
the dry ice into gaseous carbon dioxide. A significant number of students, when asked to
describe the phenomenon on a test later, recorded the event as a chemical reaction, because it
showed the indications of a chemical reaction, despite the fact that they also knew that there was
no chemical change in the transformation from solid carbon dioxide to gas.
6.0 Implications for Teaching the Nature of Science
Recent science education reform documents emphasize the importance of a scientifically
literate population (AAAS, 1993; NRC, 1996). An aspect of science literacy is having a sound
understanding of the nature of science (NOS) (Rutherford & Ahlgren, 1990; Nuhfer &
Mosbrucker, 2007). Though NOS does not have a hard and fast definition, it encompasses ideas
including how science as a process works, the epistemology of science, how scientists behave as
a social group, and how science both affects and is affected by society. (For a discussion of
these ideas, see Clough, 1997, McComas, Clough, and Almazroa, 1998, and Rutherford and
Ahlgren ,1990). To enhance NOS instruction for students, these understandings need to become
a facet of science teacher education. Lederman (1999) stated that teachers who know the
importance of teaching NOS may be less likely to ignore this content when making their
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instructional decisions. Abd-El-Khalick and Lederman (2000) draw an analogy between the
importance of NOS cognitive outcomes and the outcomes aimed at general content
understanding, and Ackerson and Abd-El-Khalick (2003) continue the analogy by emphasizing
the importance of treating explicit NOS instruction within a teacher education program in
relation to other content instructional strategies. However, Abd-El-Khalick (2001) found that
NOS instruction was more effective with students in a science content course, as opposed to a
science methods course.
Although literature shows that students will not pick up NOS understandings from
implicit, contextualized activities (facets of NOS “built in” to the content) alone (Khishfe, &
Abd-El-Khalick, 2002; Lederman, 1999), what has shown effectiveness is intermittently
utilizing decontextualized NOS activities – namely, black box activities or any other example of
NOS understandings that are not connected to course content (Clough, 2003), and instruction
which offers explicit (Khishfe, & Abd-El-Khalick, 2002) and prolonged (Clough, 1997)
contextualized NOS activities.
In his book comparing model construction in scientists to model construction in students,
Clement (2008) makes the following claim:
[M]any of the powerful reasoning and learning processes used by experts to
achieve scientific understandings are also helpful in helping students learn
scientific understandings. This parallel occurs in each of the three major
categories of applying intuitively grounded knowledge, analogical reasoning, and
model construction… (author’s emphasis) (p. 2)
With the emphasis of the instructional cycle on model evolution, inquiry, development
and justification of claims from observational data, the learning environment very much parallels
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the learning taking place in the scientific community. It was with this in mind that we distributed
a copy of the model of the instructional cycle to all students at the beginning of the semester, and
again around the mid-term. In both instances, we reviewed the various steps along the cycle, the
activities and goals at each stage, and discussed some of the parallels between how their
scientific knowledge will be created and how scientific knowledge is created by scientists. Our
rationale was that by having students become aware of and reflecting on how they are learning
and that their learning parallels how scientists learn, they would have the necessary explicit and
prolonged exposure to certain NOS concepts as called for by Khishfe, and Abd-El-Khalick
(2002) and Clough (1997) to develop their NOS understandings. Additionally, the purposeful
use of models within instruction can aid in meeting this end. Snir, Smith, and Raz (2003) argue
“that a central element of science teaching should be about metaconcepts as well as relevant
concepts. That is, students should understand what a model is and how it is used in science. We
believe that if this is done constantly as each new concept is introduced in science,
students…will be able to understand science as a way of thinking which they can apply to their
everyday world” (p. 802). It was our hope to foster this outcome by utilizing and explaining the
models during instruction and by repeatedly drawing students’ attention to their own model
development and expression.
6.1
Explicit, Decontextualized Activities
We employed a few decontectualized NOS activities and discussions to highlight several
aspects of NOS. The first was an activity involving a cube with an arrangement of names and
numbers on five sides. The sixth side was the bottom of the cube, and hidden from view.
During the activity, students worked in groups and looked at the five exposed sides of a cube to
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delineate any patterns. The object of the activity was for students to predict what was on the
bottom of the cube. They were never allowed to see what was on the bottom, but only make a
prediction and defend it to the rest of the class. We also discussed, through the use of optical
illusions, how their senses, brain, and past experiences are sources of bias in making both
observations and inferences. (For a more detailed description of this, see Remis and Dolphin,
2008).
6.2
Explicit, Contextualized Activities
As part of the instruction, students received a list of five questions from the VNOS-C
(Abd-El-Khalick, 1998; Lederman, Schwartz, Abd-El-Khalick, & Bell, 2001) all dealing with
various NOS aspects (Figure 8). Questions focused on NOS understandings having to do with
science as a discipline of inquiry, the acquisition of scientific knowledge, the tentative yet
durable nature of scientific knowledge, and the difference between scientific laws and scientific
theories. The purpose of the questions was to raise students’ awareness of their own mental
model of science. We were explicit about this purpose with them. We asked them to answer the
questions and to return to them weekly to confirm or modify their understandings based on their
activities in class. Their final assignment was to address three of the five questions within an
essay with claims about the nature of science supported by evidence from class work and
discussions (Appendix A).
Instruction concerning different types of models took place prior to the NOS questions.
We discussed the importance of their mental models and how learning happens when their
mental models change and grow in sophistication. We also explored the different purposes of
models - one being to describe phenomena and the other being to explain phenomena. We drew
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the connection between their descriptive models, such as describing the change in pressure of an
enclosed gas when the volume if its container is changed, and scientific laws (i.e., Boyle’s Law).
We also highlighted the connection between their explanation of why the gas pressure changes
with volume and scientific theories (i.e., Kinetic Molecular Theory). Lastly, we emphasized that
their mental models were the starting point of experimentation. Their experimental predictions
would be based on this model. If the prediction withstood testing, then it would remain as is; if it
failed, their model would have to be changed. Again, we sought student awareness of the
parallels between their learning and how scientific knowledge is created.
We distributed the NOS questions to the students at the mid-term of the semester, after
the nature of matter unit, as we started instruction concerning force and motion. Most instruction
was done through open inquiry, following the structure of the instructional model. Students
explored concepts such as the physics of pendulums, floating and sinking, rubber band airplane
flight and catapults. Students developed testable questions with predictions and rationalized
them based on their prior understanding. In groups of three or four students, they designed and
executed several experiments to test their predictions, all the while recording everything in their
own science notebooks. After several class periods of experimentation, students developed
claims that were supported by their accumulated evidence. They then created a mediated artifact
in the form of a PowerPoint slide demonstrating their claim and evidence. The students, in their
groups, then presented their claims to the rest of the class for discussion.
6.3 Student Learning and Science Knowledge Creation
As part of their final exam, students were asked to draw a comparison between the
process of their learning with that of scientific knowledge creation. After analyzing answers to
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this question, some themes began to emerge with regard to student understanding of NOS.
Students’ answers contained various aspects of both the acquisition metaphor and participation
metaphor of learning, but there was only subtle evidence of the knowledge creation metaphor.
Some student responses appear below.
6.3.a

acquisition metaphor
[A]fter finding that only the length of the pendulum affects the period we had to alter our
mental models, and after scientists conduct experiments the reflect on their results and
can make minor tweaks to their theories or claims.

I did not throw out my first model of the nature of matter. I mearly [sic] added on
specific information about the phases of matter that I learned in class.
These students saw their learning as being individual. For instance, based on the comment
above, this student changed her mental model by adding on to it based on what she learned in
class; a process of the individual. The comments also reflect that this is how they see the
creation of science knowledge where “scientists…make minor tweaks to their theories or claims”
based on experimentation and reflection.
6.3.b participation metaphor

In the scientific process, scientists often collaborate with one another to discuss their
findings and/or debate them. As illustrated above, in class we used large group (class)
discussions to clarify and expand our ideas.
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
In class, after dividing and experimenting, we regroup to discuss results. The
collaboration allows for a group development of understanding of what’s been done, and
individuals can contribute thoughts from their own mental model.
These students recorded their awareness that the learning they came as a result of the group
processes taking place in the class, and were able to relate that to the way scientists create new
scientific knowledge as well. They saw the importance of discussions to “clarify and expand
ideas” on the way to a “group development of understanding.”
6.3.c

knowledge creation metaphor
I had certain ideas in my head. I tested these ideas and explored my results, then
discussed with my classmates. These discussions triggered new questions to explore and
thus my learning continued (emphasis mine).
This student did not see getting an answer or making a claim as an endpoint. She saw it as a
springboard to new questions and continual learning. Although students in the small groups did
work individually and cooperatively to create entries in their science notebooks and
cooperatively on their class presentation of claims and evidence, they did not seem to internalize
that the knowledge they created as part of their notebook or presentation was part of the learning
process. It seems that their idea of making a presentation is showing what they know and not
that they participated in a generative process where learning took place during the creation of the
artifact. I was not explicit with students about how learning is mediated by the production of
such artifacts. Klein (2004) argued that “without such explicit discussion, students may assume
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that the purpose of a writing assignment is to improve their communication skills, or even to test
their knowledge of a topic, rather than to learn” (p. 225).
Students’ Views of the Nature of Science
6.4
As was stated earlier, we made explicit reference to the nature of science throughout the
second half of the course through the use of a series of questions. The questions were to elicit
their prior knowledge of the nature of science. We had them revisit the questions often to
reassess their own understandings within the context of the activities they had done and the
learning they had achieved. From the final essay they wrote recounting the evolution of their
understandings of NOS, we observed positive changes in their understandings of what science
was, how it worked, the difference between laws and theories, and the tentative, yet durable
nature of scientific knowledge. Data in the form of student quotes from their essay support this
claim.
6.4.a What is science?

I depicted science as a static thing that was to be learned and strived for. However, now I
view the nature of science as an ongoing, dynamic process that is systematic in its
approach to gather observations for knowledge (emphasis in original).

I used to think science was finding the answer…I now feel that science is a process of
observation, finding patterns, making predictions, and continually adding to knowledge…

I used to think that science was a way…to find absolute truths. I have now learned that
science is in fact the ability to predict based on the advancement of our own mental
models.
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These quotes indicate an understanding of science as being a dynamic process; a process that
ends not with ‘absolute truths” but continually adds to the knowledge base. Their descriptions of
how science works, viz. “a process of observation, finding patterns, [and] making predictions
reflects nicely the types of activities that the students participated in while performing the
experiments during class.
6.4.b Ideas about Experiments

I used to think that experiments were performed to prove something true, however now I
know that the data we collect from experiments are use to support a claim.

I used to think that an experiment was testing a hypothesis and controlling a test or
investigation. I now understand that an experiment is a way of investigating a question
and finding evidence to support a claim. Claims are models that we build on and our
evidence is what we gain through observation.

I also believed that an experiment was simply for finding evidence to support claims. I
did not take into account the processes of observation and prediction.
A common misconception about science is that the role of experiments is to “prove something
true.” This was an idea held by most of the students. The quotes above indicate a softening of
this type of scientism. These students see the goal of experiments as producing evidence that
ultimately supports a claim, and that the claim is really a model built by humans.
6.4.c Law? Theory? What’s the difference?

My own mental model holds examples of the differences between laws and theories. In
my mental model, the explanatory claims I observed are theories. The presence of atoms
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in my mental model, for example, is a theory. I cannot physically see atoms and
molecules, but evidence about them has been previously gathered…My mental model
does hold laws, however. Descriptive relationships, such as the relationship between
string length and pendulum period in our pendulum experiment is a scientific law.
This student eloquently draws the distinction between laws and theories, where laws are
descriptions of physical relationships and theories are more explanatory and try to tell why such
a relationship might exist. This is very different from the common misconception which sees
scientific laws as being an absolute and unchanging truth; something that has been proved, and
scientific theories which are seen as an educated guess waiting for enough evidence from testing,
to eventually become a law. This student was also able to draw the parallel between her own
descriptive and explanatory mental models and larger scale laws and theories.
6.4.d The Durability of Scientific Knowledge

Although scientific knowledge is supported by an abundance of data from repeated trials,
it is not considered the final answer. Scientific knowledge is flexible. Scientists
continually test and challenge previous assumptions and findings.

…the theory of evolution does not change, but fossil and othe[r] discoveries can enhance
the theory and generate more knowledge.

…scientific theories evolve as new technologies are made available.
These quotes are examples that demonstrate student understanding of the durable, yet tentative
nature of scientific knowledge. This is in mark contrast to the commonly held precept that
scientific knowledge is ultimate and unchanging. Students show awareness that when new
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information comes along that does not support the current scientific explanations, the
explanations must be modified. Having had to do this with their own understanding through the
course may have helped them to draw that conclusion. They also indicated an understanding that
developments in technology could help to enhance abilities to observe, allowing for the new data
to be collected.
So as not to paint a completely rosy picture of results, similar to Abd-El-Khalick (2001)
that the majority of students did not move just slightly from the idea that science was the
uncovering of formal truths by completely objective scientists, to a more moderate understanding
of the human aspects of scientists and the tentative yet durable nature of scientific knowledge.
Instead they left the realm of scientism for the idea that “scientific knowledge as ‘someone’s
opinion about what’s going on’” (Abd-El-Khalick, 2001, 229). We were able, however, by
drawing attention to their won learning as a parallel to the creation of knowledge by scientists, to
get them to see and articulate a more sophisticated view of the scientific process.
7.0
Discussion and Conclusions
This pilot study has shown that the educational value of the proposed instructional model
holds promise from both the standpoint of students learning in the content domain as well as in
the domain of NOS understandings. There was an obvious increase in sophistication in students’
mental models regarding the particulate nature of matter. They were also able to recognize their
simplistic understandings of science as being “static” and a “search for truth” and come to
understand it as a process; a human endeavor. In some cases, the implications of science being
“human,” namely its tentative nature, also came through in their writings and discussions.
Students commented on many of the strategies incorporated within the instruction, namely small
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group and whole class discussions, experimental activities where they were responsible for the
design, classmates’ presentations, and reflective assignments, as being both instrumental in their
learning and making the class challenging, yet enjoyable.
The decision to implement the instructional cycle was very last minute, only because it
was being developed just weeks before the beginning of the spring semester. This created a
situation where some pedagogical decisions had to be made in real time – not the most efficient
way to run a class. Though many of the teaching strategies presented here were already a part of
the instructional repertoire, some shifting in activities and timing still had to take place.
Hindsight, however, is usually 20/20 and there are some things that could be changed that could
make the outcomes even more powerful.
In general, students were not able to connect the fundamental principles demonstrated in
the activities to one another. Information from each activity seemed to be compartmentalized
and treated as discrete bits of knowledge. More attention should be paid by the instructor to the
order of activities and the potential of scaffolding information better, creating a story line so to
speak, where previous information is used to create new information. Student attention should
be drawn to this explicitly as well. This could also help remediate students’ general lack of
ability to make general claims which are supported by evidence. It seems that because they were
drawing from only a discrete set of data to make their claims, their claims were much more
descriptive than explanatory and much more limited in scope.
It is very important to place a greater emphasis on explicitly informing students that the
artifacts they are creating in their science notebooks and presenting to the class are not just
learning activities in their own right, but that these conceptual artifacts can and should be used as
tools for facilitating further understanding. This could be done by having the students reflect on
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their creativity and gain awareness of when they’ve utilized newly gained knowledge to further
their understanding. Also, I feel that referring them to the actual model of instruction more often
could help them be more aware of the activities they are participating in and the rationale behind
that participation so they might see how they are learning and take more control of that process.
This could help them to strengthen the analogy between their knowledge gains and those gains
made within the scientific community. They may also gain some insight into pedagogy so they
can practice these types of strategies with their future classes.
I observed many misconceptions from the students. A portion of which I feel were latent
misconceptions, anthropomorphism for example, and were not expressed in their earlier mental
models because their models were not sophisticated enough to support them. Other
misconceptions seemed to be brought about from the actual instruction. This was observed with
students considering the sublimation of dry ice as being a chemical change because they
observed some of the some of the characteristic indications of a chemical change, regardless of
the fact that they knew there was no change in the chemical nature of the substances involved.
This may be a result of the almost purely descriptive nature of students’ models. Since their
models were based mainly on observations, they lost the importance of a chemical reaction being
one where substances change into new substances and the temperature, color change and gas
production are merely indicators of such a change not the definition of the change. Von
Glasersfeld (1996) argued that “The sensory objects, no matter how ingeniously they might be
designed...no matter how trivial and obvious they might seem to the teacher, are never obvious to
the novice" (p. 311). Only mindful implementation of activities and constant monitoring of
student participation in their knowledge creation can help to minimize the occurrence of
misconceptions and facilitate meaningful learning.
37
ASTE Conference – January 2010
Glenn Dolphin – Syracuse University
grdolphi@syr.edu
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