Challenging Nave Beliefs


1
Challenging Naïve Beliefs

• Patrick Bush

2
Examples of Naïve Beliefs

• Persistence of Motion Theory

One of the problems in instruction is that
learners come to problems with naïve beliefs
which must be corrected in order for new
learning and understanding to take place. These
naïve beliefs are the subject of this lecture.
3
Possible Explanations Why Naïve Beliefs Persist

• Parental
• instruction/
• social expectations

Improper Scientific Instruction
Preconceptions or biases
Parents often show a gender bias in how much they
teach their children about scientific
explanations this bias tends to favor males
(Crowley 2001).
4
Improper Scientific Instruction
When people are unskilled at scientific
techniques they often have problems separating
theory and evidence into discrete groups. Those
with that problem can be separated into one of
two groups.
Data-Bound Individuals
Theory-Bound Individuals
5
Improper Scientific Instruction
Theory bound Those who will distort evidence to
fit the theory they follow. Usually through
applying incorrect causal relationships or
accepting theories based on insufficient evidence.
Data Bound
6
Improper Scientific Instruction
Theory bound
Data bound Those who will distort or adjust the
theory to fit the data theyve found. These
individuals have difficulty working backward from
given evidence to the theory that might explain
this evidence or what the evidence would mean to
the theory.
7
An Example of Theory Bound Individuals Reasoning
Given the hypothetical example balls which
varied in size color texture and the presence
of ridges were served and then placed in boxes
based on how well they flew when served. The
results are shown below
Good Serve
Bad Serve
(Do these results help more to show that one
person is right) Texture because you have more
balls that have smooth texture that came out with
more bad serves than you do balls that have rough
texture and bad serves. (Do these results prove
that Mr. T is right) Yes because the balls with
smooth texture large and small have bad serves.
(What do the results have to say about Mr. Rs
view) Its not showing nothing about ridges.
(Why not) Because you have balls that have
ridges that have bad serves and balls that have
ridges that have good serves. (Kuhn 88) Both
groups have the same number of each
(ridged/textured) balls. Two different
strategies are being used on identical evidence
one being causal (texture) the other being non
causal (ridges).
8
This example shows how learners tend to
instantiate pieces of evidence as an instance or
example of one particular theory rather than
looking at the evidence as a unit in itself that
can possibly be applied to several theories.
9
Example of a Data-bound Individuals Reasoning

• Referring to the previous example a learner
  began with the impression that color made no
  difference but was then asked to provide
  evidence supporting the opposite.

Good Serve
Bad Serve
(Can you explain how this proves that color
makes a difference) These dark in the good
basket are more visible in the air. You could
see them better. (Kuhn 88) In this example the
learner changed her theory to fit the evidence
instead of maintaining her theory and realizing
that the evidence provided didnt match her
theory.
10
There Are Two Explanations for the Biases
Learners Make When Reasoning
Ego-defensiveness
Cognitive Interference
11
Ego-defensive Explanations for Reasoning Biases

• Evidence for or against ones theories can have an
  impact on self-esteem which in turn effects
  ones motivation to investigate the evidence.

• Individuals
• sometimes are overcritical of
  belief-challenging evidence

Belief- threatening evidence
High intrinsic accuracy motivation
Valid rejection of evidence
and casually accept belief-affirming evidence
Low intrinsic accuracy motivation
Belief- enhancing evidence
Uncritical Acceptance of evidence
12
Cognitive Explanations for Reasoning Biases

• People often have preconceived causal theories
  about how things work and the persistence of
  naïve beliefs is due to individuals inability to
  decontextualize theory and evidence and when
  confronted with belief challenging evidence
  people reinterpret the evidence to preserve their
  biases.
• Belief-affirming evidence is quickly and
  effortlessly interpreted which can lead to more
  cognitive interference (factors irrelevant to the
  reasoning task) on the person

Belief- enhancing evidence
Uncritical Acceptance of evidence
high cognitive interference
whereas belief-threatening evidence will draw
more focused attention which will result in less
cognitive interference and more in-depth scrutiny
of the evidence
Belief- threatening evidence
Low cognitive interference
Valid rejection of evidence
13
Consolidated Model of Biased Scientific Reasoning
age
Low intrinsic accuracy motivation/ high cognitive
interference
Belief- enhancing evidence
Uncritical Acceptance of evidence
Scientific reasoning competence
Belief- relevant evidence
Potential variables inhibiting interference
Preservation of existing belief system
Ego protective motivations
Theoretical belief system
Belief- threatening evidence
High intrinsic accuracy motivation/ low cognitive
interference
Valid rejection of evidence
Scientific reasoning competence seems to be the
most likely to change so that is what an
instructor should look at to eliminate naïve
beliefs.
14
Improving Scientific Reasoning

• Evidence is often thought of as an instance or
  illustration of a theory rather than a separate
  entity. Evidence and theories should be presented
  as separate entities so that relationships can be
  formed with separateness in mind.
• Students should examine what the evidence would
  mean for the theory (this would require thinking
  about the theory as a cognitive object rather
  than just a tool to reach a certain conclusion)
  this should be regardless of whether one accepts
  the theory or not so it would help bring ones
  own preconceived biases into light.

15
Control of Variables Strategy

• Developed by Chen and Klahr (1999) CVS is a
  domain general strategy for teaching how to
  design good experiments. The crux of the
  strategy is that you teach people to design
  experiments where all variables are controlled
  for save the one that is being tested which
  allows for a valid causal inference to be made on
  the subject at hand

So far these strategies have only been focused on
prevention. For changing preexisting naïve
beliefs one can use Conceptual Change theory.
16
Beliefs About Knowledge Without a Science Context