Pedagogical Constructivism: Neuroscientific Evidence and

Implementation in Science Classrooms

JoAnna Brown

Department of Chemistry and Biochemistry

Brigham Young University, Provo, Utah 84602

719-580-3321

Fax: 801-422-0153

joanna.brown@byu.net

Abstract

Pedagogical constructivism is the teaching philosophy that knowledge is constructed in

the mind of the learner upon the learner’s prior knowledge. This teaching philosophy has been

successfully implemented in science classrooms. Students enter classrooms with different past

experiences that cause them to interpret information differently. Educators need to be aware of

this and draw out and correct any misconceptions students may have. This can be done through

personalized learning and peer instruction. Peer instruction also allows students to learn from

their peers who are in the process of learning the same information, rather than from a teacher

who may, unintentionally, apply hindsight bias. Past experience and knowledge is organized in

the brain in cognitive schemas. If students can assimilate new information with pre-existing

schemas, they are able to learn new information more quickly. Neuroscientists are beginning to

discover evidence for constructivist teaching methods through research on schemas and the

effects of repetition. When a person learns, neurons fire in the brain and oligodendrocytes

increase myelination on the activated axons. The more these pathways are traveled, the more

myelination occurs. Myelin increases conductivity along neural pathways—used to store

information in schemas—and allows that information to be accessed more quickly providing

faster recall times and increased memory. By incorporating prior knowledge and repetition in

science classrooms, students can learn difficult concepts more effectively.

Contents

Introduction......................................................................................................................................1

Opinions on Knowledge..............................................................................................................1

The Brain.....................................................................................................................................3

Classroom Applications of Constructivism.....................................................................................4

The Curse of Knowledge.............................................................................................................4

Misconceptions Facilitate Learning.............................................................................................6

Teaching Methods.......................................................................................................................9

Neuroscientific Evidence for Cognitive Schemas.........................................................................11

Conclusions....................................................................................................................................14

References......................................................................................................................................16

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Introduction

Opinions on Knowledge

Beginning with Socrates and Plato,1 philosophers have defined knowledge as justified,

true belief. This tri-tiered definition has caused many debates on what it means to know

something and what can actually be known. The traditional view of knowledge,2 realism, is that

to know something, the learner’s mind must contain an exact replica of reality and, therefore,

everyone’s knowledge is, and must be, exactly the same. This view suggests that we have an

idea of what goes into a person’s mind (stimulus) and what comes out (response), but we don’t

understand what goes on inside the brain during the learning process. It also suggests that this

process is irrelevant as long as the same conclusion is reached for all learners and they have a

copy of reality in their minds. Bodner,3 a constructivist, doesn’t agree with this philosophy;

instead, he suggests that we do know what is inside our minds and that a learner constructs

knowledge from given stimuli and previous experience. The learner simply tries to create

knowledge that “fits” with what is perceived as reality. This “fit” is much like how a key fits

into a lock; keys of many different shapes can open a given lock as long as the main points are

correct. Bodner says, “Each of us builds our own view of reality by trying to find order in the

chaos of signals that impinge on our senses. The only thing that matters is whether the

knowledge we construct from this information functions satisfactorily in the context in which it

arises.”

Lionni4 illustrated the idea of constructivism in his children’s book Fish is Fish. This

story is about a tadpole and a fish who are childhood friends. Over time, the tadpole grows into

a frog and goes to explore dry land. He returns to tell his friend, the fish, all about his adventures

and describes things he saw—cows, people, birds. The fish, having never lived above water,

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tries to imagine what these might look like. He pictures people as fish wearing clothes and

walking on their tail fins. The bird he imagines as a fish with beautiful wings, and the cow he

pictures as a fish with spotted fur and pink udders. Trying to imagine something he had never

seen before, he had to build on the knowledge he already had constructed of reality.

Bransford et al.5 says that students come to formal education with a wide range of prior

knowledge, skills, and beliefs that significantly influence what they notice about their

environment and how they organize and interpret information being taught and presented therein.

This is contrary to the “tabula rasa” philosophy of teaching and learning that suggests student

minds are blank slates teachers are to fill with information. Bodner3 argues that information

can’t simply be transferred unscathed from the mind of the teacher to the mind of the learner, but

that it needs to be built and organized in the mind of the learner to be remembered and used.

Jonassen6 pointed out that research in cognitive psychology utilized models from

cognitive science to construct theories about learning processes that supported this idea of

constructivism. Research is now beginning to investigate how people learn,7 how students

construct knowledge, and how education shapes the human mind,8 rather than on necessary

teaching skills9 and how to best get information into students’ minds.10

Kant11 believed that the brain is an active participant in constructing experience. He said

that our brain perceives our environment at each moment in time. It then applies “categories” to

these temporal slices to organize them to create experience. Piaget12 is credited with bringing

Kant’s idea of categories to cognitive psychology. He proposed the idea of a cognitive structure

called a “schema” in which related memories and knowledge are stored. He said that when we

encounter new information, we try to fit it with knowledge we already have in existing schemas.

If this new information fits, assimilation occurs and this new information is organized

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accordingly; if this information does not fit, then a process called accommodation occurs and an

existing schema is changed to allow for this new, differing information.

Neuroscientists are discovering evidence for these cognitive schemas, and this

information might help educators know how to best teach their students. A new area of research,

educational neuroscience, focuses on applying what is known about the brain to education. This

information can be useful in teaching, but there is some caution surrounding this area of study.

Multiple reviews13-18 point out the need for interdisciplinary training to establish successful

collaboration among neuroscientists and educators. This could help eliminate neurological

myths being cultivated that are based on misunderstandings, oversimplification, and premature

applications of neuroscience to a classroom. Neuroscientists are also cautious because lab results

can differ from observations in social situations. Lee17 calls for reliable research tools that focus

on interactions among brain, mind, and behavior to help bridge these gaps.

Pedagogical constructivism19 has been shown to be successful in science classrooms.

This review examines some of the results of implementation and also discusses the recent

advances in neuroscience that may support these constructivist teaching methods based on

repetition and prior knowledge organized into schemas. As teachers become aware of the

existence of schemas—in themselves and in their students—and how the brain processes

information, they may be able to recognize their hindsight bias and better help students construct

knowledge upon their existing past experience.

Classroom Applications of Constructivism

The Curse of Knowledge

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Newton20 performed an experiment with a group of volunteers she divided into “tappers”

and “listeners”. Each tapper was given a list of 25 well-known songs and was told to choose a

song and tap out the rhythm of the melody for a listener who would try to guess what song was

being tapped. Before the experiment, the tapper was to predict whether or not the listener would

guess the song correctly and what percentage of total listeners would be able to correctly identify

the song. On average, the tappers predicted that the listeners would be able to correctly identify

the song around 50 percent of the time; however, only 2.5 percent of the 120 songs (n = 3)

presented were identified correctly. This phenomenon is called hindsight bias or “The Curse of

Knowledge”. Massaro21 defines this as the tendency to see events that have already happened as

more predictable than they actually were before happening. This causes people to be biased by

their own knowledge when trying to understand others’ naïve or uninformed perspectives.

Bernstein et al.22 showed that this phenomenon appears in children and adults. Young

children, between the ages of three and five (n = 36, M = 55.5 months, range = 40 – 69 months,

22 female), and undergraduate students (n = 16, adult, eight female) were shown 32 images of

common objects on a computer screen that started out blurry and gradually became clear by

either the pixel or blur method shown in Figure 3. They were asked to judge when a peer would

accurately be able to identify each object. In both age groups, half of the participants were told

the identity of the objects prior to the experiment and the other half were not. Hindsight bias was

calculated as the ratio of the identification point of those with a priori knowledge divided by the

identification point of those without it. A ratio above 1.0 indicates hindsight bias, and the 95

percent confidence interval did not include 1.0 for any group. The average of the four groups’

hindsight bias ratios was 1.91 ± 0.22 and 1.69 ± 0.19 for the blur and pixel methods,

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respectively. Those who were told the identity beforehand overestimated the ability of someone

without this a priori knowledge to accurately identify the object.

Teachers teach material years after they first learned it. They have already developed

cognitive schemas for the information they are teaching and their hindsight bias can cause them

to struggle to relate to an obstacle students may be facing in understanding a concept that is new

to them. Chi23 investigated this idea and asked experts (professors) and novices (students) to

group physics problems into different categories. The novices grouped the problems according

to surface features such as the object in the problem (e.g., spring, pulley, inclined plane, etc.),

whereas the experts grouped the problems based on principles they would apply to solve the

problem (e.g., conservation of linear and angular momentum, statics, Newton’s second law,

conservation of energy, etc.). The professors had developed schema over years of solving

physics problems and were able to look at the big picture, deduce the method necessary to solve

the problem, interpret which information in the problem was useful, and categorize it

accordingly. The students didn’t have these schema in place, so they looked at the information

that was given and tried to make connections to equations they had memorized to try to

determine what steps to take and how to use these equations to get to the correct answer.

Bodner24 suggests that the difference between a problem and an exercise is the level of

familiarity. What is a novel problem to one may be a routine exercise to another. Teachers see

the problems they present to their students as exercises, but the students see them as problems.

He says that problem solving is “what you do when you don’t know what to do”.

Misconceptions Facilitate Learning

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Because students enter the classroom with preexisting schemas, teachers need to

understand how to address any preconceptions or misconceptions students may have before

trying to teach them new information. If they are not addressed, students will incorrectly

assimilate information to existing schemas rather than accommodate their schemas to fit the new

information. Brumby25 discusses how young children often believe that all moving things are

alive. Vosniadou et al.26 showed that some students came into her class thinking the earth was

flat. After being taught that it was actually round, they all seemed to understand; but, upon

interviewing the children, she found that they had constructed the incorrect idea that the earth

was flat and round like a pancake rather than round like a sphere. If teachers don’t have their

students discuss what they are learning to draw out these misconceptions, the teacher may not

even know they exist.

Champagne et al.,27 Brumby,25 and Gunstone et al.28 showed that students can appear to

have scientific knowledge and do well on standard exams given in a classroom, but when

presented with unfamiliar problems or real-life examples they often resort back to naïve

misconceptions they had when they first entered the classroom.

When Bodner and co-workers29 asked organic chemistry students to predict the products

of organic chemistry reactions, they were able to do so, but when asked to show the mechanism

of the same reaction, they weren’t able to come up with the answer as easily. The students had

simply memorized reactions without understanding the interactions taking place that would be

second-nature to an expert organic chemist. Similarly, when he30 asked general chemistry

students to draw Lewis dot structures, they performed the task with ease. When the same

students were asked to show what was happening with the electrons during a chemical reaction,

they were unable to make this connection. One student was able to come to a correct conclusion,

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but used incorrect logic. Misconceptions and misunderstandings can still exist and make the

student believe that what they know is true, when it actually might not be.

If these misconceptions are drawn out in the classroom through discussion or what

Piaget12 called disequilibration, they can actually help the student learn and accommodate the

new information into their existing schemas. Bodner2 explains that when a student comes to this

point of disequilibration, or a knowledge gap, they realize that there is a disconnect between

what they thought to be true and what they’re being taught and become motivated to understand

why. van Kesteren31 says this prediction error is a key factor that drives learning and that this

novelty of information and accommodation with an existing schema generally improves memory

of the new information.

Another way to draw out misconceptions in science classrooms is through

demonstrations. Mazur and co-workers32 showed that when demonstrations are used in a

classroom and students are simply required to passively observe, they learn little or nothing at all

from them and they are no better off in understanding the underlying concept than a student who

hadn’t seen the demonstration at all. One out of every five students was shown to even

remember the demonstration inaccurately and remember it coming to an incorrect conclusion.33

When the students were taught the concept before being shown the demonstration and were

given time to think and predict what was going to happen and draw on prior knowledge before

seeing the demonstration, more were able to accurately remember the outcome of the

demonstration. Roth et al.34 showed that only four out of ten students remembered the correct

outcome of a demonstration on angular momentum in a follow-up interview, and only three out

of ten were able to show it as a vector the way it was shown during the lecture demonstration.

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When demonstrations are used constructively, they become more useful as a learning/teaching

tool rather than entertainment.

The verbal-linguistic and visual representations used in classrooms need to be connected

to reality. Without relating new information—chemical reactions—with previous knowledge—

Lewis dot diagrams—the students may not make these connections on their own even though

they may seem second-nature to the teacher. If the information is only used and discussed in the

unit in which it is presented for the first time, it won’t be remembered as well as if it is connected

to previously-learned material.

Teaching Methods

Overcoming hindsight bias and misconceptions can be difficult. Mazur and co-workers35-

38 suggest implementing peer-instruction in the classroom to help combat these learning and

teaching obstacles. This allows students the opportunity to reteach the material to their peers.

During this time of discussion, they can help each other overcome learning barriers that they

have just overcome themselves. This also allows for each student to get personalized instruction

which can bring out any misconceptions they may have on the topic.

Table 1 describes an inquiry-based teaching model called the 5E Learning Cycle that has

been implemented in science classrooms at the high school39 and undergraduate40 level. This

method consists of five parts: engage, explore, explain, elaborate, and evaluate. The engagement

and exploration portion of the learning cycle allows all students to have a common starting point

to use and refer back to as their prior knowledge as they have discussions while learning the new

topic. Once the learning cycle is completed, the students will have had multiple opportunities to

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have discussions about the information with their peers and have the new information presented

to them multiple times in a variety of ways.

Maxwell and co-workers41 noticed that Maxwell’s organic chemistry students seemed to

consistently receive low exam scores when tested on spectroscopy in her second semester

organic chemistry class. Because of this, they analyzed current editions of organic chemistry

textbooks and found that most introduced the analyzing of spectra around chapter 12.

Traditionally, professors teach this topic during the second semester of an organic chemistry

sequence so that students will first be familiar with common structures, functional groups, and

relationships within molecules before learning this difficult skill. This method of teaching these

topics wasn’t benefitting Maxwell’s students so she decided to implement a new, constructivist

teaching strategy and introduce IR spectroscopy and 1H NMR spectrometry during the first week

of the first semester of her organic chemistry sequence. Table 2 discusses the evolution of her

teaching method over the years that she used this method. During the first semester of the

sequence, students were to match IR absorptions to functional group, create 1H NMR correlation

chart, and circle the correct structure that these correlated to on the homework from four

multiple-choice answers. During the second semester, they were to draw and name a compound,

calculate the index of hydrogen deficiency, identify important peaks in IR, and show correlation

charts for NMR when given molecular formula and either IR and 1H NMR or 1H NMR and 13C

NMR. Students were tested on these topics during each semester. Thirty-five percent of the

first-semester final exam was multiple-choice spectra questions; the second-semester final exam

was eighty percent spectra with free response questions. Figure 4 shows the students’ exam

scores during second semesters and Figure 5 shows the trend of the percentage of the class that

passed the exam with a score of 70 percent or higher and the percentage that failed. Over the

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years, exam scores improved while Maxwell taught using this method. In 2008, she had

developed a large enough question bank to allow each student to have a unique homework set

and eliminate cheating.

Bodner42 used this same idea by relating the way he taught multiple topics in

undergraduate chemistry classes. He related the common-ion effect of buffers and the effect of

LeChatelier’s principle on salt solubility. He also used similar tables and examples when

showing conjugate pairs in RedOx reactions and Brønsted acid-base reactions by showing how

both involve the transfer of particles, both involve relative strengths of conjugate pairs, both have

methods of determining whether or not a reaction will happen based on relative strengths of

oxidizing/reducing agents and acids/bases and what the relative strength of the conjugate will be,

and both have constants—cell potentials and equilibrium constants—that can help make

predictions about the reactions as well. When he began making these connections in his

classroom, 95 percent of students were able to answer the following question correctly on an

exam:

“NaHCO3 (aq) can be used to neutralize strong bases, such as NaOH. What conclusion can be drawn from the fact that the following acid-base reaction proceeds to the right as written?

HCO3–(aq) + OH–(aq) ↔ CO3

2–(aq) + H2O(l)

(a) HCO3– is a stronger acid than H2O

(b) HCO3– is a stronger base than CO3

2–

(c) HCO3– is a stronger base than OH–

(d) CO32– is a stronger base than OH–

(e) H2O is a stronger acid than HCO3– ”

Neuroscientific Evidence for Cognitive Schemas

When a brain is presented with any type of information, neurons are activated. The

human brain consists of approximately 100 billion neurons through which electrical and

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chemical signals travel.43 Figure 1 shows the basic structure of a neuron. These nerve cells

contain all the features of a normal, human cell within the cell body. Connected to the cell body

is the axon, which makes up about 95 percent of the volume of the cell; in humans, the axon can

be up to one meter long.44 The axon is connected to the cell body by the axon hillock and is

surrounded by a lipid material called myelin,45 which acts as a conductor for electrical

impulses.46 Neural signals, action potentials consisting of sodium and potassium ions,47-48

generate in the axon hillock and travel through the myelinated axon to axon terminals where they

are transferred as chemical neurotransmitters across synapses to other nerve cells. Dendrites

branch off from the cell body in many different directions and are where these signals are

received. This propagation of signals through myelinated axons and dendrites allows for the

transmission of information across hundreds of neurons at speeds up to 100 m/s.44

Axons are myelinated through their interactions with another cell type in the brain called

neuroglia, or simply glia. Oligodendrocytes are the glial cells that myelinate axons in the central

nervous system, and they often interact with multiple axons at one time.49 Figure 2 shows an

oligodendrocyte myelinating axons. To do this, the glial cell comes in contact with the activated

axon(s), becomes flat, and winds the lipid membrane around the axon(s). This creates multiple

insulating layers that increase axonal conductivity. The more a certain pathway of axons is used,

the more it is myelinated; this pathway of least resistance is what neurons will transmit

information through when a similar experience is encountered. Javanbakht50 says these pathways

are the physical structures associated with the idea of cognitive schemas that develop and

become myelinated during learning and exposure to new experiences.

McKenzie et al.51 showed that as rats learn, information is presented to the hippocampus

through the firing of neurons and is organized into schemas where it is stored with existing

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related memories. Ten rats were trained to choose a specific item depending on the context they

were placed in—item X in context 0 and item Y in context 00. After 7.0 ± 0.7 days and 202 ±

23.8 trials (mean ± SE), the rats were able to perform the tasks in the different contexts with an

accuracy above 80 percent (n = 83) for 12 consecutive trials. Number of trials to criterion were

strongly correlated (r = 0.995, p < 0.0004). In subsequent trials, items X and Y were replaced

first with items A and B, then with items C and D, and the rats were trained to perform the same

task with these new objects within the same contexts. Nine of the ten rats were able to perform

the task above 80 percent with the new object sets with fewer trials than the original XY set

(69.6 ± 13.1 for AB and 70.6 ± 3.8 for CD) with an accuracy above 80 percent after the first day

(XY versus AB p = 0.008, AB versus XY p = 0.002, AB versus CD p > 0.05). The rats had

acquired a general schema for the association by completing the initial problem. This allowed

them to relate the new object tasks in the same context back to the schema already developed and

the prior knowledge acquired. Although they were presented with different objects, they were

able to perform the task in a shorter amount of time because it was presented to them in a context

they were familiar with.

Heusser et al.52 also showed that prior exposure to a concept can aid in the subsequent

processing of that same information. He analyzed 16 volunteers—seven male and nine female—

who were all healthy, native English-speakers. Each person was presented with an initial

stimulus (i.e., a spoken noun, a picture of an object or scene, or a written noun) and up to four

(mean 2.5) various subsequent stimuli in which the initial stimulus was repeated in the either the

same (1/3 of the time) or a different modality (2/3 of the time). There were three within-modal

conditions (SS—spoken nouns preceded by spoken nouns, PP—pictures preceded by pictures,

WW—written nouns preceded by written nouns) and 6 cross-modal conditions (PS—spoken

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nouns preceded by pictures, WS—spoken nouns preceded by written nouns, SP—pictures

preceded by spoken nouns, WP—pictures preceded by written nouns, PW—written nouns

preceded by pictures, SW—written nouns preceded by spoken nouns). The volunteers were

presented with 285 items, grouped into 9 sets of 26 items each, and were to indicate, by pressing

a button as quickly as they could, whether the item presented was natural or manmade. The

items were presented in a continuous stream; pictures and written nouns were presented for 0.25

s and spoken nouns varied from 0.5 s to 1.0 s depending on the length of the word. Correct

answers in the initial presentations went up significantly from 90.79 percent (SD = 0.04) on the

initial presentation of the repeated object to 94.45 percent (SD = 0.03; paired t-test p < 0.0001)

on the repeated presentation. Overall, participants were faster in answering the question the

second time the item was presented to them (all ps < 0.05). Imaging of the brain also showed

that there was a suppression in brain activity in many regions of the brain during the second

presentation of the item. This was especially true in the perirhinal cortex (PRc) which may

contribute to storing conceptual information and receives auditory, visual, and somatosensory

inputs from other regions of the brain, including the posterior parahippocampal cortex. This

suggests that information may be received and organized in the hippocampus, since it is the part

of the brain attributed with organizing new information and creating memories, and then sent to

the PRc for assimilation or accommodation to be stored in long-term memory since short-term

memory only holds about seven items of information.53 Researchers31, 54-56 have also proposed

association among the hippocampus as well as the medial prefrontal cortex (mPFC) and medial

temporal lobe (MTL) as they become long-term memories through a process called SLIMM

(schema-linked interactions between medial prefrontal and medial temporal regions).

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Javanbakht50 says these patterns are later used in recognition when encountering a new

experience to encode, consolidate, and retrieve information. Within SLIMM (and adaptive

resonance theory), it is thought that the main function of the mPFC is to determine resonance.

This means it detects congruency between new information and existing information held within

schemas in the neocortex. The more a pathway or pattern is utilized, the more stabilized and

fixated it becomes and the speed of access as well as memorability is increased. This increased

speed of the action potential through the neural pathway is due to increased myelination of the

axons used.

Mechanisms for oligodendrocyte selectivity have been proposed,57 but the precise

mechanism is still unknown. It has been demonstrated58-61 that axonal activity while learning a

new skill promotes oligodendrocyte progenitor cell (OPC) proliferation as well as increased

myelination by mature oligodendrocytes in the area of the brain where neural firing is occurring

in both rats and humans.

Conclusions

What is known about how the brain utilizes schemas in storing, organizing, and recalling

information may help teachers understand how their students learn and, thus, how to best design

instruction for their science classrooms.

Teachers are able to come to conclusions much faster than students because they have

myelinated the necessary neural pathways over and over again, and students haven’t even

developed these neural connections yet.

There is no quick-fix solution or direct procedures educators can rely on for teaching, but

developments from neuroscience can be used to aid teachers in understanding how the brain

processes information. More research needs to be done to accurately identify the mechanisms

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that signal myelination of axons, but it has been shown that axonal activity promotes

myelination. When students learn something for the first time, they will either associate or

assimilate that information within existing schemas where memories and knowledge are stored.

Instructors need to remember that students don’t have these schema in place and forming them

takes time, repetition, practice, and correcting of misconceptions. As more research is done and

better research methods are developed allowing experiments to be reliable in a lab as well as in

social situations, the neuroscience behind learning will be better understood.

There will always be a need for some degree of lecturing in the classroom, but teachers

need to transition away from the traditional method of teaching where the all eyes are at the front

of the room while busy hands scribble down notes the students will later memorize and

regurgitate on exams; this is not conducive to how the brain assimilates and accommodates

information into existing schemas. When motor skills are at work alongside learning, more

neurons are firing causing more mental activity and more myelination of axons which allows for

quicker recall. Students need to be able to interact with each other during class and have

common starting points to use as a basis from which to build new knowledge upon. New

information also needs to be presented more than once so that schemas can form and at

subsequent times be drawn from to assimilate new information.

As educators and neuroscientists begin to collaborate, great progress will be seen in

education systems because teachers will be able to understand how their students’ minds will

learn best and allow them to not only be successful on exams, but be able to use the scientific

knowledge gained in the classroom in everyday situations because it has been assimilated into

schema triggered by their day to day interactions.

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Table 1. Descriptions of the steps of the 5E learning cyclea

Engagement Captures attention, promotes thinking raises questions, identifies misconceptions; generate comments, makes connection with prior knowledge

Exploration Poses questions that allow students to test ideas, hypotheses, and alternatives; students make observations, collect data and reach decisions

Explanation Traditional teaching phase; past experiences are used to explain terms and concepts; students use observations and evidence to create and test explanations

Elaboration Deepens understanding by using concepts in new situations; students apply knowledge and skills in a new but similar situation

Evaluation Pre, formative, and post assessments occur throughout the learning cycle

a Information from Ref. 46

Table 2. Evolution of Maxwell’s constructive teaching method in organic chemistry coursesa

  Homework Problems

First UsedSemester

in Sequence Lecture Time (h)Number of Questions Answer Type Problem Sets

Summer 2002 2 9 10 Free response Identical

Fall2002

1 6 20 Multiple-choice with reasoning Some duplicates

2 6 – 8 20 Free response Some duplicates

Spring 20081 6 20 Multiple-choice with

reasoning Some duplicates

2 6 – 8 20 Free Response Unique

Spring 20091 6 20 Multiple-choice with

reasoning Unique

2 6 – 8 20 Free Response Unique

a Information from Ref. 48

Figure Captions

Figure 1. Structure of a neuron. Adapted from ref. 20 with permission from instructor.

Figure 2. Representation of oligodendrocyte myelinating an axon. Adapted from ref. 21 with

permission from instructor.

Figure 3. When testing the effect of hindsight bias, participants viewed images gradually

becoming clearer in the blur (left) and pixel (right) method. Adapted from ref. 29 with

permission from instructor.

Figure 4. Final exam scores during second semesters of Maxwell’s organic chemistry classes

before and after implementation of the constructive teaching method of introducing spectroscopy

during the first week of the first semester of the organic chemistry sequence. Data from ref. 48.

Figure 5. Overall trend in passing and failing exam scores during second semesters of

Maxwell’s organic chemistry classes before and after implementation of the constructive

teaching method of introducing spectroscopy during the first week of the first semester of the

organic chemistry sequence. Passing score is 70 percent or above. Data from ref. 48.

Figure 1

Axon Terminal

Figure 2

Figure 3

Figure 4

Figure 5