Evidence for the effectiveness of inquiry based, particulate-level

Evidence for the Effectiveness of Inquiry-Based, Particulate-Level
Instruction on Conceptions of the Particulate Nature of Matter
Chad A. Bridle*,†
and Ellen J. Yezierski‡
†
Science Department, Grandville High School, Grandville, Michigan 49418, United States
‡
Department of Chemistry and Biochemistry, Miami University, Oxford, Ohio 45056, United States
ABSTRACT: Research has shown that students in traditional college-preparatory
chemistry courses become masters of mathematical equations without an
understanding of the conceptual basis for the mathematical relationships. This
problem is rooted not only in what curriculum is presented to students, but also in
how it is experienced by the students. Ample evidence exists in support of both
inquiry-based instruction and the use of particulate-level models in instruction as a
means for improving students’ conceptual understandings in chemistry. Little
evidence exists, though, for the effectiveness of an instructional model that involves
the merger of these two methods. In an effort to address this gap, a series of
laboratory and classroom activities was created that blended guided inquiry-based
instructional practices with particulate-level modeling experiences. The content of
the curriculum focused exclusively on phases of matter and chemical versus
physical changes in matter. This research explores the novel curriculum’s effect on
student understanding of the particulate nature of matter in two sections of high school chemistry. Qualitative and quantitative
evidence supporting the curriculum is presented.
KEYWORDS: High School/Introductory Chemistry, Chemical Education Research, Hands-On Learning/Manipulatives,
Inquiry-Based/Discovery Learning, Constructivism
FEATURE: Chemical Education Research
■ INTRODUCTION
Chemistry students have long demonstrated their ability to
solve algebraic problems without a clear understanding of the
conceptual background of the problem.1−4
This lack of a
scientifically accurate conceptual framework for the very
foundations of chemistry is not only a problem by itself, but
its effects extend into all other aspects of student performance
in chemistry.5
Two different approaches to this issue have been
explored: curriculum focused on particulate-level representa-
tions of matter,6,7
and inquiry-based instructional models.8,9
This paper describes the implementation and effectiveness of a
novel curriculum that merges particulate-level modeling with
inquiry-based instruction.
■ BACKGROUND
Johnstone describes the three different levels of representation
in chemistry: macroscopic, submicroscopic, and symbolic.10
A
particulate understanding of atoms and their properties is
central to explaining any concept that is observed or described
on the macroscopic or symbolic levels.11
The importance of a
strong understanding of the particulate nature of matter must
be considered carefully. How do we appropriately represent
and describe the particulate level? What sort of prior knowledge
of the particulate level do students bring to the classroom?
How do instructors properly guide their students to an
appropriate understanding of the particulate nature of matter?
Because the particulate world of chemistry is invisible and
theoretical, descriptions of this level must include models. In
using models, the ability of the learner to comprehend the
meaning of the model must be considered. Harrison and
Treagust describe three different ability levels.12
At the most
basic level, learners interpret models as exact replicas of reality.
Thus, an atom that is represented as a red circle actually is a red
circle. As modeling ability increases, students become better at
differentiating between what a model is intended to show about
a situation and the limitations of the model. In a later study,
Harrison and Treagust describe a successful method for
employing atomic models in instruction.13
Their work showed
that part of the instructional process must involve exploring and
discussing the merits and limitations of a particular model.
Similarly, students bring varying degrees of understanding
about the basic behaviors of matter. As far as incorrect
conceptions about atoms and molecules, students frequently
struggle with size, shape, and composition.14
These mis-
conceptions include the assumption that one can see atoms and
molecules under a microscope, that their volume and weight
can change depending on conditions, and, for example, that
water molecules can contain atoms other than hydrogen and
oxygen. This lack of clarity leads to struggles with classification
of matter, such as being able to distinguish between compounds
and mixtures.15
Considering physical changes in matter,
Published: December 14, 2011
Article
pubs.acs.org/jchemeduc
© 2011 American Chemical Society and
Division of Chemical Education, Inc. 192 dx.doi.org/10.1021/ed100735u | J. Chem. Educ. 2012, 89, 192−198
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copying and redistribution of the article or any adaptations for non-commercial purposes.

common misconceptions include the idea that boiling liquids
involves the expansion of molecules or even the breaking and
forming of chemical bonds within the molecules.16,17
Lastly,
these misconceptions lead to students’ inability to distinguish
clearly between physical and chemical changes in matter.18
This evidence suggests that appropriate instruction in this
field is a matter of constructing a correct conceptual framework
within the minds of the students and not simply memorizing
facts and processes. Using inquiry-based instructional ap-
proaches in chemistry has been proven effective. Hewson and
Hewson used inquiry instruction in the design and
implementation of curriculum regarding the concepts of
mass, volume, and density.19
They found a statistically
significant improvement not only in correct conceptual
understandings, but also in a reduced number of misconcep-
tions. Similar positive results were found by Lewis and Lewis
upon implementing a peer-led guided inquiry curriculum.9
The literature shows that both particulate-level instruction
and inquiry-based pedagogy improve students’ conceptual
understanding of chemistry. Gabel suggested both methods
for improving conceptual understanding, but little research
exists regarding the merger of these two instructional models.20
The evidence within the literature merits the exploration of the
fusion of the two methods in a novel inquiry-based, particulate-
level curriculum.
■ THEORETICAL FRAMEWORK
The design of the intervention and the overall study is guided
by learning theories grounded in work by Piaget and more
recent constructivist points of view, including the conceptual
change model. DeBoer noted that the purpose of science
education goes beyond simply supplying students with facts
and figures.21
Students must be able to think like scientists:
effectively using their scientific knowledge, carefully studying
and observing their world, and developing new understandings
from these observations. Piaget’s theory of how humans
constructed knowledge caused educators to reconsider how
content was delivered. Prior models of instruction assumed that
the information presented by the teacher was simply transferred
to students, as though they were a blank sheet of paper waiting
to be filled. Piaget forced educators to consider learning from
the learner’s perspective. He believed that not only did each
learner construct his or her own understanding of a subject
individually, but also that any new knowledge had to be
integrated with the learner’s current framework of under-
standing.22
In regard to the particulate nature of matter,
students cannot simply be given information about the invisible
particulate universe and be expected to accept it. Instead,
students must explore and construct their own understandings
of the topic so that a specific representation of the atomic level
fits with their understandings of the world.23
This model for
instruction parallels not only Piaget’s theory of student
development, but also the philosophies of science research.24
Learners and researchers alike approach a new situation with
their current conceptual framework. Any new information or
findings may not fit with their current framework. Individuals
must then construct a new framework that accommodates the
new knowledge and can be accepted as reasonable and useful.
The process of constructing a true, correct understanding of the
nature of matter allows students to more accurately describe
any novel situations they may experience within and beyond
chemistry. This approach to chemistry instruction, grounded in
constructivist learning theories, necessitates the use of instruc-
tional and laboratory techniques that allow students to explore
and find meaning in a given situation.20
■ RESEARCH DESIGN
This pilot study aimed to investigate the effectiveness of
inquiry-based, particulate modeling experiences in improving
students’ conceptual understanding of chemistry. Using a quasi-
experimental, primarily quantitative study with a one-group
pretest−posttest design,25
the intervention engaged students in
inquiry-based activities with various particulate-level represen-
tations of matter early in the school year. The curriculum
implemented in the study was designed by a team of chemistry
educators as part of Grand Valley State University’s Target
Inquiry teacher professional development program. The
classroom activities were designed to be used in the first few
weeks of an introductory chemistry course. These laboratory
experiences were intended to provide students with a strong
particulate-level, conceptually based understanding of the basic
behaviors of matter, better equipping them for further learning
activities in chemistry.
■ CONTEXT
The novel curriculum was implemented in two high school
chemistry sections in a large, suburban high school in the
Midwest United States. One of the authors (Bridle) was the
instructor for the two chemistry sections that were studied.
Both sections were exposed to the same curriculum; data were
not compared to a control group or established norms. The
population in 3rd hour, n = 26, included 13 female and 13 male
participants, while the population in 4th hour, n = 28, consisted
of 13 female and 15 male participants. The participants were
15−17 years old, predominantly Caucasian and middle class.
The curriculum was implemented during five and one-half 60-
min instructional periods over a three-week period as described
in Table 1.
■ DESCRIPTION OF INTERVENTIONS
Describing and Categorizing Matter Using
Particulate-Level Models
The teacher guide and student guide for Putting the World in a
Box26
are available as cited through the Target Inquiry Web
Table 1. Summary of Inquiry Activities Implemented
Inquiry Activity Description
Instructional
Time, Min.
Putting the World in a
Box
Constructing an understanding of appropriate particulate-level modeling. Establishing particulate-level descriptions of
solids, liquids, gases, elements, compounds, and mixtures. Establishing appropriate methods for categorizing matter.
120
Change You Can
Believe In
Establishing clear, particulate-level definitions for physical changes and chemical changes. 90
The Only Thing
Constant in Life Is
Change
Establishing an appropriate connection between particulate-level definitions of physical and chemical changes, and
macroscopic observations.
120
Journal of Chemical Education Article
dx.doi.org/10.1021/ed100735u | J. Chem. Educ. 2012, 89, 192−198193

site. This activity was designed to specifically target
misconceptions related to the description and categorization
of matter. The content addressed in this activity was the
students’ first exposure to particulate-level models in their
chemistry course. The literature describes students’ varying
abilities to appropriately interact with models and how this may
affect student learning regarding particulate-level instruc-
tion.12,13
As a result, a significant portion of the activity calls
for students to explore the usefulness and limitations of various
particulate-level representations of matter such that students
may construct an understanding of the particulate-level
behaviors of solids, liquids, and gases as they relate to
observable, macroscopic behaviors. Second, the students use a
similar approach to establish particulate- and macroscopic-level
knowledge of elements, compounds, and mixtures. Lastly, the
activity aims to merge these two knowledge structures in an
effort to establish appropriate procedures for describing and
classifying matter. Students explore the similarities and
differences between elements, compounds, and mixtures and
construct an appropriate classification scheme for particulate-
level representations of matter.
Constructing a Particulate-Level Conception of Physical
and Chemical Changes
The activity Change You Can Believe In27
is the first of two
activities, both available as cited through the Target Inquiry
Web site, that address the concepts of physical and chemical
changes. This activity uses cards that illustrate particulate-level
examples of physical and chemical changes. Figure 1 is a sample
card, representing the single replacement reaction between
magnesium metal and a hydrochloric acid solution.
Students were not given information about what substances
or processes were represented by each card. This was
intentional, so as to prevent students from falling back on
their macroscopic understandings and experiences to describe
particulate-level situations. Students consider the cards with
only their prior knowledge as a basis and categorize the cards as
either physical or chemical changes. The student guides were
constructed in such a way that led to discussion and debate
between students. This process, guided by the instructor,
allowed students to modify and clarify their particulate-level
understanding of physical and chemical changes.
Constructing a Symbolic and Macroscopic Conception of
Physical and Chemical Changes
The Only Thing Constant in Life Is Change28
was the second
activity intended to address the concepts of physical and
chemical changes. Students performed actual macroscopic
examples of the processes represented by the physical and
chemical changes cards. A more traditional laboratory approach
would have students make macroscopic observations and then
ask them to relate these observations to the particulate level.
This second activity reversed this process. Students have
already categorized the laboratory activities as physical or
chemical changes in the previous activity. For example, the
students would have classified the process in Figure 1 as a
chemical change. When this reaction is performed in the
laboratory, one observation students would make would be the
evolution of a gas. Students then make macroscopic
observations of all of the processes illustrated in the cards
and analyze their observations to determine the usefulness of
each type of observation in defining an observed process as
physical or chemical. For example, students would consider
whether the evolution of a gas was a sign of a physical change, a
chemical change, both, or neither. In the case of gas evolution,
whether the production of steam, a gas, from boiling water fits
this same category caused students to consider limitations and
precise definitions for their macroscopic observations. This
alternative approach forced students to use macroscopic
observations as tools for constructing a model of particulate-
level behavior. A more traditional approach may have led
students to consider the production of a gas, for example, as a
definitive sign of a chemical change. The new approach results
in students concluding that particulate-level definitions of
physical and chemical changes are much more reliable
descriptors of macroscopic processes.
Instruments and Data Collection
In determining the effectiveness of the activities in bringing
about conceptual understanding, a published conceptual
chemistry instrument, Particulate Nature of Matter (ParNo-
MA), was used.29
The instrument is a 20-question, multiple-
choice test specifically focusing on students’ concepts at the
particulate level related to phases of matter and phase changes.
Each question addresses an aspect of the particulate behavior of
matter, with distracters being directly related to common
misconceptions. The authors of the instrument report 100%
validity of the appropriate correct responses when examined by
several of their colleagues as well as establishing the internal
consistency of the instrument when administered to an
introductory college chemistry section, N = 72, Cronbach’s α
= 0.78.
Students in this study were given the instrument both as a
pretest and posttest in order to measure any changes in their
conceptual framework. Student scores were reported as a
percent of the number of questions they correctly answered out
of 20. After obtaining parental consent and student assent
according to the permissions granted by the Human Research
Review Committee at Grand Valley State University, the
pretest was administered to students during the first few days of
the course. Students experienced the treatment curriculum
during the third through fifth weeks of the course, and the
posttest was then administered in a similar fashion during the
ninth week, at the end of the marking period. The significant
gap in time between the pretest, the treatment, and the posttest
limits any test−retest bias.
On the basis of the data from this instrument, structured
interviews were conducted with five students during the second
semester of the course, 4 months after the treatment and 3
months after the posttest, to probe specific concepts. The
significant time lapse from the treatment was intended with the
hope that the knowledge structures of the participants revealed
Figure 1. Sample activity card from Change You Can Believe In
depicting the reaction of Mg(s) with HCl(aq) at the particulate level.

in the interviews reflected their long-term understandings.
Following an analysis of student gains on the ParNoMA, five
students from both class periods were selected as potential
participants in the interview based on the gains they
experienced. One participant experienced no gain (0%) in his
ParNoMA score, three students experienced moderate gains
(15−20%), and one experienced large gains (50%).
The protocol began with participants being presented with a
clear liquid (water) boiling on a hot plate. The interview
protocol did not describe the substance as water to avoid any
prior knowledge bias of water’s behavior. The beaker contained
water, though, for practical purposes. A small plate of glass was
placed above the boiling liquid and condensation collected on
the glass. Students were then provided with a pictorial
representation of the situation that included several call-outs,
or zoomed-in views, of the situation (Figure 2). The three call-
outs referred to particulate behaviors within the beaker,
between the beaker and the glass, and at the surface of the
glass. Students were told that the substance in the beaker
consisted of a compound comprising two elements, A and B.
They were provided with small, blue triangles that represented
atoms of element A and yellow squares that represented atoms
of element B. The instructor constructed a particulate-level
representation of the compound, consisting of one of each
atom.
The participants were then asked to construct and describe
what they believed the particulate-level behavior of the
substance would be in each of the call-outs. The instructor
recorded video of the students modeling their ideas, including
audio of their descriptions. The protocol also asked students to
describe the changes the substance experienced and to identify
them as physical or chemical changes.
■ RESULTS AND DISCUSSION
ParNoMA Results
Statistical analyses using SPSS software were conducted to
determine whether any changes in student scores, reported as
percentages, between pre- and posttest occurred. While
itemized responses for each question were obtained, individual
questions on this survey have not been established as reliable
measures of individual concepts. Thus, probing individual
questions for further information about student understanding
was not pursued.
The data were collected from two different sections of the
course. The authors wished to consider both data sets together,
so the appropriateness of consolidation was considered first.
Statistical analyses were conducted on student gains between
pre- and posttest (posttest minus pretest). An Anderson−
Darling test for normality was performed on each section using
student gains. The test, which is optimal for small samples,
showed that results from both periods, 3rd hour with p =
0.0755, and 4th hour with p = 0.349, could be considered
normally distributed.
As shown in Table 2, mean student pre- and posttest scores
for each class do appear different. A test for equivalence was
carried out to determine whether a priori differences existed
between the two different class periods. The analysis of the
ParNoMA pretest scores was done using two, one-tailed t-tests
as prescribed by Lewis and Lewis.30
Results showed that the
two groups could not be considered statistically equivalent to
each other. The differences between these two populations may
lie in which students get scheduled in each hour. The
complexity of the high school scheduling process often allows
for honors or elective classes to only be offered during certain
hours. This often results in specific populations of students
unintentionally remaining grouped together in other classes.
This phenomenon may be at the root of the difference.
Considering each section individually, a paired samples t-test
was used to explore differences in student pre- and posttest
scores. As summarized in Table 3, students in 3rd hour did not
show a significant improvement in score, while 4th hour results
did show a statistically significant improvement, p = 0.011. The
standardized effect size index (Cohen’s d) for 4th hour was
0.51, indicating that the intervention produced a medium effect.
A power analysis using G*Power 3.1.2 revealed that the sample
size for each period was too small to detect a small effect. This
is important in drawing inferences from 3rd hour results. Figure
3 further illustrates student gains, showing the pretest and
posttest means and 95% confidence intervals for 3rd and 4th
hour results individually. This graph illustrates that both classes
achieved similar results on the posttest, despite 4th hour
students starting with a much lower mean pretest score.
The statistically significant difference between pre- and
posttest ParNoMA means for 4th hour warranted further
Figure 2. Diagram used during interviews for participants to illustrate
their particulate-level understanding of phenomena depicted: Water
boiling in a beaker, evaporating, and then condensing on a glass plate.
Table 2. Means and Standard Deviations for ParNoMA
Scores by Class Period
Pretest Scores, % Posttest Scores, %
Class Period (N) Mean SD Mean SD
third Period (26) 40.58 14.92 43.65 20.13
fourth Period (28) 34.82 15.30 44.46 23.43
Table 3. Student Gains by Percent: Paired Samples t-Test
Class Period
(N)
Mean
Difference SD 95% CI
F
Values
p Values (Two-
Tailed)
3rd Period
(26)
3.07 13.42 [2.34,
8.50]
1.17 0.253
4th Period
(28)
9.64 18.75 [2.37,
16.91]
2.72 0.011

considerations. A Pearson correlation between pre- and posttest
scores showed a significant moderate positive correlation,
0.601, p = 0.001. This relationship suggests that participants
who performed well on the pretest also performed well on the
posttest. This result shows some relationship between a
participant’s prior knowledge and their resulting knowledge
after the described treatment. A second Pearson correlation
between student pretest scores and student normalized gains
[(post − pre)/(100% − pre)] on the ParNoMA showed no
significant relationship, 0.036, p = 0.854. This suggests that the
amount of conceptual gain, as evidenced by the normalized gain
on the ParNoMA, was not dependent on the participant’s
pretest score, independent of the absolute magnitude of the
gain. Thus, students with a strong prior knowledge, while
performing at a higher level on the posttest, did not
demonstrate a greater gain in knowledge than students with
weak prior knowledge.
While the observed gains on the ParNoMA may seem
meager, one must consider them within the broader view of the
students’ educational experience. Prior to these students
beginning this course, they had a well-established conceptual
framework for how to describe and classify matter. To modify
any one piece of a student’s misconception about matter,
several steps must take place. Students must be presented with
a situation that runs counter to their current framework. They
must then be allowed an avenue to explore and make sense of
the new information and formulate a new, correct conception.
Such modification does not guarantee a correct conception, as
the student may establish a new, yet still incorrect, conception
that incorporates the dissonant situation.24
If one takes this
snapshot of the Piagetian learning process and expands it to all
of the concepts that fall into description and classification of
matter, the cognitive load on the student becomes immense.
Furthermore, students are not likely to have had any effective,
appropriate instruction in particulate-level behaviors prior to
their experience in this course.31
As a pilot study without a control group, the data describe
the effectiveness of the curriculum as it pertains to the sample
and the instructor of the course. Thus, these results do not
provide direct evidence for the novel curriculum over a
traditional model, nor do they speak to the effectiveness of the
curriculum in another setting. These results do, however, show
that the novel curriculum had a positive effect on student
conceptions regarding the particulate nature of matter as it
pertains to phases of matter and changes in matter for students
in the 4th hour class in our setting.
Structured Interview Results and Discussion
The researcher attempted to obtain as much of a representative
sample of the study population as possible through the
selection of participants with diverse conceptions about the
particulate nature of matter. Table 4 represents the participants’
pre- and posttest scores on the ParNoMA.
Audio and video recordings of participant responses were
collected. Analysis and coding of the data focused on
connecting participant responses to either correct conceptions
or to previously identified misconceptions. The video coding
software HyperRESEARCH32
was used to organize video clips
and look for patterns.
Representation of States of Matter at the Particulate Level
The substance in the beaker and the condensate on the glass
should have each been identified and represented as a liquid.
Correct representations included particles placed in close
proximity to each other, but still allowing for freedom for
particle movement. The liquid should have also lacked any sort
of organized structure. With each of the five participants
providing either a correct or incorrect construction for the two
locations, 7 of the 10 models were deemed correct. Several
examples of correct participant descriptions are given below.
“It’s in the liquid form so it’d be close but still have enough
room to move around.”
(Allison)
“In here it’s going to be more of a consistently or evenly
spread out liquid.”
(Emily)
The three incorrect participant descriptions either involved
an incorrect identification of the phase of matter that was
observed or a description that did not clearly demonstrate that
the participant understood liquid behavior on the particulate
level.
The substance between the beaker and the glass plate should
have been correctly identified as a gas. Correct descriptions
needed to include the fact that the particles were spaced
significantly further apart than those of the liquid. Correct
participant models frequently accomplished this by using fewer
particles. Of the five potential participant responses, four were
identified as correct. The only participant response that was
Figure 3. Student pretest and posttest mean scores (%) and 95%
confidence intervals on the ParNoMA, broken down by class period.
Table 4. ParNoMA Results for Interview Participants
ParNoMA Score
Participant (pseudonym) Pretest Score, % Posttest Score, %
Nate 20 35
Emily 25 45
Kyle 35 50
Ryan 40 40
Allison 45 95

marked incorrect did not clearly distinguish between the
particle spacing of the liquid and the gas.
Representation of Changes at the Particulate Level
Each participant’s model gave insight into how he or she
thought the process he or she was observing at the macroscopic
level affected the connectivity of particles. In representing the
change that occurs between the heated liquid in the beaker and
the space above the liquid, all participants chose to break the
substance apart into its elements, which is incorrect and one of
the hallmarks of this particular misconception. Interestingly,
four of the five participants cited the heating process as the
cause of the decomposition of the compound.
“They undergo a chemical reaction because it’s heated.”
(Nate)
“They break down because of the heat and it makes the
atoms go faster and they break their bonds.”
(Kyle)
“They boil, which breaks the bonds to make them a gas.”
(Ryan)
All of the participants then oppositely showed the atoms
recombining to form the original compound when they cooled
and condensed on the glass. In each case, the elements were
combined such that they were identical to those on the beaker.
“Then the glass cools down the substance and they form back
together”
(Kyle)
Thus, participants seemed to recognize that the substance on
the glass and the substance in the beaker were identical.
Identification of Changes at the Particulate Level
Participants were also asked to describe each of the changes as
physical or chemical and provide a rationale for their decisions.
All participants decomposed the substance in the transition to
the gas phase and then reformed it on the glass surface. Thus,
all participant diagrams represented chemical changes. Four of
the five participants correctly identified and described their
model as a chemical change taking place. Participant responses
were identified as correct if they referenced bonds being broken
and formed or if they referenced the formation of new
substances.
“Chemical change because there’s a different substance
formed.”
(Nate)
“Chemical, because the bonds broke.”
(Kyle)
“It’d be a chemical change because it’s breaking up the
compound into two different things.”
(Allison)
Participants seem to have a clear understanding of how
physical and chemical changes differ on the particulate level,
even though their conception of what actually occurred with
the particles was incorrect.
■ CHANGES AT THE MACROSCOPIC LEVEL
Participants were asked to describe the macroscopic process of
the substance boiling (which was set up in front of them) as a
physical or chemical change. Four of the five participants
correctly identified the process as a physical change.
Appropriate justifications for such a response included
recognizing that simple phase changes were occurring.
“Physical, because it’s changing from a liquid to a gas and
then back to a liquid”
(Kyle)
“I think it would be a physical change because it’s going from
a liquid to a gas to a liquid again so it’s the physical
properties of the substance.”
(Allison)
Such a response was in conflict with the participants’
particulate models and appeared to cause some cognitive
dissonance for most of the participants.
“A physical change because...well...maybe a chemical change
because it’s being heated...so...well...actually I think it would
be a physical change because it’s just water evaporating it
looks like.”
(Nate)
Through their hesitant responses and body language,
participants seemed to recognize that their descriptions of the
changes on the macroscopic and particulate levels should have
matched, although none of them explicitly made that statement.
In summary, participants generally produced correct
descriptions of liquids and gases at the particulate level.
Participants could also clearly distinguish between chemical and
physical changes at the particulate level. When asked to identify
the macroscopic process as a physical or chemical change, all of
the participants seemed to recognize that their macroscopic and
particulate descriptions should have matched. Thus, it seems
the piece that the participants were missing was the difference
in strength between a chemical bond and intermolecular forces.
The implications of this misunderstanding are far-reaching in
an introductory chemistry course, as much of the traditional
curriculum involves processes in an aqueous solution. The
differentiation between the dissolution of a substance and any
chemical reactions it may participate in while in solution
requires a mental separation of processes involving intermo-
lecular forces and processes that involve the breaking and
forming of chemical bonds. Further consideration about how to
appropriately establish a correct understanding regarding this
conception is necessary. Furthermore, tools to assess the
student conceptions involved in the distinction would need to
be developed so that curricula could be evaluated appropriately.
■ CONCLUSIONS
Both the qualitative and quantitative results of this study
provide support for the positive effect of the novel curriculum
on developing students’ conceptual understanding of chemistry.
As a pilot study without a control group, the data describe the
effectiveness of the treatment curriculum as it pertains to the
selected population and the instructor of the course. These
results are not intended to prove superiority of the novel
curriculum over other models, but merely to demonstrate its
ability to positively affect student conceptions. As previously
mentioned, the uncontrollable aspects of the high school

schedule may have contributed to the differences between the
two sections. The scope of this study was to determine the
effectiveness of the curriculum and not necessarily how the
curriculum functioned within specific student populations.
Understanding the specific differences between the two
sections in this study may provide insight into how the
curriculum could be modified to be more effective for specific
student populations. Thus, further research into the effect of
the curriculum on different student populations is warranted.
The results of this study provide evidence for the
effectiveness of the curriculum within a specific population.
Further evidence would be required to make inferences about
the performance of the curriculum in comparison to other
curricula and in other school settings. First, a stronger argument
for the novel curriculum could be made if it were shown more
effective in concept building than a traditional model. This
would require implementing the curriculum described here
while simultaneously teaching a more traditional curriculum to
an equivalent student population. However, providing
instruction that may be inferior for the purpose of an
experimental control may raise ethical concerns surrounding
the teaching and learning beliefs of the instructor. Second,
while the researchers expect minimal variation among different
student groups, how an instructor implements the curriculum
has been previously shown to significantly influence the
potency of the curriculum.33−35
As such, an exploration of
how both different student populations and different
instructors affect outcomes due to the curriculum could
provide support for the broader use of the curriculum and
others designed around similar frameworks.
■ AUTHOR INFORMATION
Corresponding Author
*E-mail: cbridle1@gpsk12.net.
■ ACKNOWLEDGMENTS
We wish to thank the faculty and students of Grand Valley
State University’s Target Inquiry Program for their input and
collaboration in this effort. We are grateful for the willing
participation of the students of Grandville High School. This
material is based upon research and professional development
supported by the National Science Foundation (ESI-0553215)
and the Target Inquiry Program at Grand Valley State
University. Any opinions, findings, and conclusions or
recommendations expressed in this publication are those of
the authors and do not necessarily reflect the views of the
National Science Foundation or Grand Valley State University.
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