In society today
technology is all around us. Every job
utilizes computers in one way or another, from cashiers in grocery stores to
executives in corporations. It is our
duty as teachers to prepare our students for life as productive citizens.
Social
studies classrooms must be able to meet the demands of the new electronic or
knowledge society. Students will need to
develop communication, critical thinking, problem solving, and interpersonal
skills. These skills translate into the
human capital that individuals carry with them as they move through economic
society. Possession of these skills
allows individuals to confidently pursue knowledge-related jobs and
opportunities. Using technology in
social studies and other curriculum areas is important because the workplace
will demand skills that relate to computer use” (Stanley,
213).
To that end, in the past 20 years, there has been a
push toward implementing computer instruction into the curriculum. This has been accomplished through the
creation of computer labs and mini-labs in mainstream classrooms. Teachers have been instructing computing
skills as well as teaching general subject areas through the incorporation of
technology. There has been considerable
debate regarding the effectiveness of instruction through the computer. This is known as ‘The Digital Divide’.
The federal government has recently taken notice of
the importance of technology in the classroom.
The government has invested in E-Rate, a grant program which provides
funding for economically challenged primary and secondary schools to purchase
hardware and telecommunications products.
The growing
recognition of the importance of new telecommunication technologies came at a
time of growing concern over the ‘digital divide’ separating individuals and
communities that have access to these tools from those that do not. Although Congress was not ready in1996 to
include advanced services to the home as key component of universal service,
lawmakers did see public access to these tools in schools and libraries as a
stepping stone to developing a modern communications infrastructure in
communities. Faced with the likelihood
that the latest information and communications tools probably would not reach
our public schools and local libraries for a long time, policymakers felt compelled
to take steps to meet the infrastructure needs of these institutions
(Carvin, 5).
As a teacher my
lessons depend on technology; I am the computer coordinator. It is not only my responsibility to teach
students how to use technology and how to learn through technology, but also to
teach my fellow teachers how use technology as a tool within their
classrooms.
Many teachers are
intimidated by technology. When asked,
some teachers told me that they felt as if they were not needed anymore if the
Internet can do everything. My response
was that the Internet is too vast to be navigated without a teacher’s
guidance. The majority answered with,
“well that is not in the curriculum” and felt as though they do not have the
time to do the necessary research.
I find software on
CD-ROMs to work well for teachers who are fearful or apprehensive. CDs are virtually foolproof, very
user-friendly, and allow for the use of technology in a non-threatening way. Programs on CD-ROM, such as ‘Reader Rabbit’,
read to the students and provide the teacher with dittos in order to help
students develop comprehension. These
reading programs often come in the form of units and touch on many areas of the
curriculum. Educational games also come
on CD-ROM. Many scholars disapprove of
educational games, mostly because they are ‘drill and kill’. From my own observations, students tend to
become bored quickly by these games because there is not much critical thinking
involved.
A program, also
available on CD-ROM, which really gets the older students excited, is called
‘Tom Snyder’s Decisions Decisions’. This
program incorporates technology with student reactions. Groups work together to solve a problem
presented by the computer. Each group of
four students role-plays to decide on each of the decisions that they
face.
When teachers use
any kind of technology inside the classroom, the lesson can get
interesting. I find laptops to be a real
attention-getter. Laptops and handheld
computers give students direct access to the software being utilized and allow
them to follow along and take notes.
"With a Palm handheld computer, a teacher or student can do amazing
things: access the Internet wirelessly, take notes, read books, calculate,
sketch ideas, collect data, access resources, manage activities and courses and
instantly beam information" (www.palm.com).
The
Internet is a source of information, a gateway to: libraries, universities,
laboratories, museums, other countries, and all sorts of other educational
resources. Social studies in particular is a subject that can be dulled by the memorization of
facts, outdated textbooks, and opinions that are ‘politically correct’. The Internet grants access to the works of
many authors and primary documents that editors may omit.
On-line historical archives offer
access to primary sources in many novel formats and allow novices to undertake
the advanced kinds of inquiry that scholars normally do, while bringing their
own questions and concerns to bear.
Communication forums on the Web enable students to participate in the
ongoing construction of historical meaning with a wide assortment of other
people. Composition and publishing tools
such as computers and camcorders enable students to visualize historical
complexities and change, and develop and express their understanding of the way
that personal and local history connect to history on a larger scale. And historical simulations place students
‘back in time’, not simply to drink up the atmosphere of a different period,
but to role-play and problem solve, and in doing so develop historical
knowledge and skills. (Bruner and Tally, 47).
The program that I
will be experimenting with is called ‘Inspiration’. This program is a concept mapping software
package, which provides students with an opportunity to work on their computer
skills as well as introducing them to the learning skills associated with concept
mapping. The students can map their
thoughts in their own format or the teacher can assign a template for students
to fill in and follow. If the students
have a hard time understanding how to use the program, there are always written
directions on the bottom of the template.
The template is a great way for teachers to give notes. If each student has a laptop or a handheld
computer they can follow along with the teacher’s notes and fill them in as
needed.
For teachers, concept maps are useful tools for analyzing and planning units of study and for identifying gaps in the curriculum. Like an architect's blueprint, a concept map represents complex ideas, their organization, and their importance. Further, concept mapping can be used to analyze textbooks, thereby revealing the suitability of the conceptual development of the text in terms of teachers' preferences and students' needs (Romance and Vitale).
The
illustration depicted below is a concept map template generated through
Inspiration software.
www.Inspiration.com
Concept mapping has been studied extensively. In most studies, concept mapping was proven to be a sound method for students to use when organizing their thought processes.
Concept mapping allows thinkers, readers, and writers to translate ideas and concepts into a visual, graphic display that they can use for reading or writing assignments. When teachers construct graphic networks on the chalkboard, overhead, or chart paper, students see how the ideas they will read or write about connect with their previous knowledge about a topic. (Sinatra, 267).
Concept mapping has been helpful inside the classroom since the 1960’s. One of the men who helped implement the use of concept maps was Professor Joseph D. Novak at Cornell University, who followed the work of David Ausubel. Ausubel believed that prior knowledge was key to learning.
Ausubel (1968) subsequently advanced a hierarchical memory theory in which new concepts and their relationships are integrated hierarchically into existing cognitive structures. Another approach to characterizing cognitive structure stems from associationist memory theory (Deese, 1962, 1965). Deese was among the first to use word association tasks to analyze components of cognitive structure. Associationist memory models are not limited to hierarchical structure, but, instead, allow for different types of relationships between concepts, including hierarchical ones. Since the 1970s, the most prevalent methods for assessing students' cognitive structures have been based on associationist theoretical foundations, including word association, card sorting, graph building, and similarity ratings (Goldsmith, Johnson, & Acton, 1991; Preece, 1976a, 1976b, 1976c; Shavelson, 1972, 1974; Shavelson & Geeslin, 1975). Studies in several domains show significant correlations between the similarity of students' and experts' cognitive structures and measures of achievement (Diekhoff, 1983; Fenker, 1975; Herl & Dennis, 1993; Shavelson & Stanton, 1975). (Herl 209).
In one study, Richard Sinatra used concept mapping in a colleague’s classroom and tracked the results. He concluded that concept mapping works especially well for at-risk students.
Over the years we have found that applying and practicing the construct implementation plan works for students at all grade levels and may benefit at-risk, low-achieving students to a high degree. Positive reading comprehension results have been shown for special education youngsters (Sinatra, Stahl-Gemake, and Berg 1984), for remedial reading students (Sinatra, Berg, and Dunn 1985), for third through fifth grade children in compensatory reading programs (Sinatra and Pizzo 1992), and for college freshman who applied maps with writing after reading selections that displayed four styles of text organization (Sinatra, Stahl-Gemake, and Morgan 1986). Stronger writing improvement was shown for some of the college freshman and also for at-risk fourth graders who wrote sequentially organized essays over a half-year or full-year period.
(Sinatra 271).
A researcher wanted to perform a study using her nursing students to determine whether concept mapping could enhance the students’ critical thinking skills.
Faculty within the culminating clinical course in a baccalaureate-nursing program elected to use concept maps to foster the links between the theoretical and clinical components of the course. Course and clinical faculty invested time in learning to use concept maps. Six senior clinical groups (n = 54) were taught to use concept maps as a learning strategy. During the first week of class, students were taught how to create concept maps. After this introductory session, students completed concept maps on the scenario given to them in class. This map was used to demonstrate their understanding of mapping, and they discussed the maps in their clinical groups. (Daley 45).
The results of Daley’s study were positive, the class did consist of some students who did not like concept mapping, but results were still positive.
Data analysis demonstrated a group mean score of 40.38 on the first concept map and 135.55 on the final concept map, for a difference of 98.16. The t value comparing the first concept map to the final concept map was -5.69 (p = .001). The data indicated a statistically significant difference between the first and final map. This difference is indicative of the students' increase in conceptual and critical thinking. (Daley 46).
Daley most likely conducted an autoregessive time series statistical analysis to measure the improvement of her subjects over time. She measured the effectiveness of concept maps with regard to critical and conceptual thinking.
The foundations and reasons for utilizing concept maps in the classroom has remained the same throughout the years, however implementation of concept maps has changed drastically from the 1960’s. A concept map can be presented many different ways, from webbing to spreadsheets. With the advancements in technology, concept mapping has become digitized.
Computers have changed the face of many paper-and-pencil tasks, not excluding concept mapping. Many researchers found that computers provide certain benefits when using them for concept mapping.
Over the past several years, the Center for Electronic Studying at the University of Oregon has been investigating the use of computers to facilitate concept mapping. Such computer-based concept mapping enables teachers and students to draw and redraw their concept maps in an electronic environment, thus making changes to a map's content and structure relatively easy. Concept mapping with a computer has greatly enhanced teachers' and students' willingness to use concept mapping for instructional purposes, because electronic maps transcend page size, are easy to create, and are dramatically faster to revise than their paper-and-pencil counterparts. (Anderson-Inman 7).
Concept mapping on the computer does have some obvious downsides, for example:
· Not all classrooms have computers.
· Many teachers are afraid or averse to using the computer.
· There are occasionally technical difficulties associated with computers.
Despite these and other issues, many people support concept mapping through technology.
Jonassen (1990) proposes that few of the computer tools used today for learning have been designed as learning tools. Usually educators use existing tools for teaching purposes. According to Jonassen, concept mapping computer tools belong to the rare category of computer tools that were designed specifically for learning. http://www.ericit.org/digests/EDO-IR-1997-05.shtml
Eric Plotnick the associate director of ERIC Clearinghouse on Information and Technology wrote an article, “A Graphical System for Understanding the Relationship between Concepts”. He explains the benefits of concept mapping and also touches on the advantages of technology when using concept mapping.
Once you have a concept map on paper, try to fit in those forgotten concepts or the ideas you came up with overnight and you will know the advantages of computer assisted concept mapping. Anderson-Inman and Zeitz (1993) compare the use of the concept mapping program "Inspiration" with the paper-and-pencil approach and found that using this program ‘encourages revisions to the concept map because deletions, additions, and changes are accomplished quickly and easily.’ (Plotnick 42).
My experience with Inspiration software has been similar to Eric Plotnik’s. I find it to be user-friendly and the students seem to like the software.
Most computer assisted concept mapping tools allow the user to point and drag a concept or group of concepts to another place on the map and automatically update all the appropriate links. (Plotnick 43).
I find this to also be true. When students want to change their maps it is easy for them. This is a great advantage because students always seem to change their minds. Paper and pencil makes the students hesitant to change their concept maps because they don’t want to erase or start over.
Once a concept map is created using a computer, the program usually allows the user to convert the map to different electronic formats. These can be vector or bitmapped images, a text outline, or even a hypertext structure. These electronic formats can then be stored, sent, manipulated, used, printed, and deleted just like any computer file. (Plotnick 43).
I have not asked students to convert their concept maps to any other programs as of yet. I currently do not see a need for doing so, although it is beneficial to have the option to save the file in different file types for greater versatility.
Computer assisted concept mapping allows for digital storage of concept maps. Digital storage takes less space, makes retrieval easier, and is especially important if concept maps will be used on a large scale. (Plotnick 43).
Storage has it’s
pro’s and con’s. Of course you can store
more on a hard drive then in your bag, but the computer cannot go with the
students. Backups are on disk but can
become damaged and/or lost. I feel that
when using a concept-mapping program, students should print their file, as well
as saving to disk, so that there is a hard copy.
My research study
centers on the effectiveness of Inspiration software for concept mapping. The importance of this study is to determine
the effectiveness of technology when incorporated into a social studies
curriculum.
Inspiration’s
program designers claim that the visual learning techniques in their software:
improves clarity in the thinking process,
reinforces understanding, integrates new knowledge, and assists students in
identifying misconceptions.
Students see how
ideas are connected and realize how information can be grouped or organized.
With visual learning, new concepts are more thoroughly and easily understood.
Students recreate, in their own words, what they've learned. This helps them
absorb and internalize new information, giving them ownership of their ideas.
Diagrams updated throughout a lesson prompt students to build upon prior
knowledge and internalize new information. By reviewing diagrams created
previously, students see how facts and ideas fit together. (http://www.inspiration.com/vlearning/index.cfm)
To test
Inspiration’s ability to enhance learning techniques, I will use the
instructions that Inspiration prescribes.
The student makeup in the school in
which this study was conducted, and the student makeup of the sample itself, is
almost entirely of Haitian descent. The
school is located in Queens, NY,
one of the five boroughs of New York City,
an urban area consisting of students who are largely recent immigrants. The school is a private, Catholic institution
but approximately 30% of the students and their families are not practicing
Catholics. All students wear a uniform
and are expected to maintain a certain level of integrity in order to continue
their enrollment. Tuition costs
approximately $3,000 a year (with discounts for siblings), however much of the
tuition is subsidized through charity.
Forty percent of the school’s student body is eligible for discounted or
free school lunch. According to E-Rate,
this school is at 80% poverty level (they double the figure to come up with
what they feel is a more accurate portrayal since many students’ families do
not file the paperwork required to label their financial status) and thus is
eligible for technology and communication grants at an 80% discount.
The sample for this study was made
up of 40 7th graders, ranging from the age of 12-14 years. The students were paired off into groups of
2. Students were asked to work with the
peer who sat next to them. Twenty-three
of the subjects were male, and 17 were female.
Nine groups were gender mixed, and 11 were same gender. Out of the 11 same-gender groups, 7 groups
were male and 4 were female. We should
assume that this sample is representative of the school as a whole’s
demographic makeup.
Two teachers were involved in
conducting this study. One teacher was a
27 year old male who had been teaching in the school for 2 years, the other was
a 24 year old female who was a first year teacher. Both of whom are the primary 7th
grade teachers and students are familiar with them.
To
begin my research study, I familiarized the students with Inspiration
software. I taught a lesson instructing
them on how to use Inspiration’s tool box, how to maneuver throughout the
program and how to create a concept map from start to finish using the
program. The students were already
familiar with concept mapping, or webbing.
They had been working with concept maps in language arts from the
beginning of the school year.
Next
I administered a pre-test to asses the students’ understanding of the
software. The topic that the pre-test
covered was Government in 1776, the start of the unit in the 7th
grade curriculum. Students were not
allowed to use textbooks or ask for a teacher’s assistance regarding the topic. I wanted to see how much knowledge they could
express on their own. They were asked to
work in groups of 2 and were allowed to refer to the teacher for assistance on
the software itself.
The first concept map was assigned to students in class 7-1
on the topic: ‘Issues that the U.S. Government faced during the 1780’s and
1790’s’. These students used Inspiration
to create their concept maps. The
students in class 7-2 used paper and pen for the same topic. The students are arranged in the same
grouping for both learning mediums. The
classes received the following directions:
1. Work
together to create a concept map on the following topic: ‘Issues that the U.S.
Government faced during the 1780’s and 1790’s’
2. Use
any material you like on the topic
3. Do
not worry about wrong information or spelling
4. Do
not ask any group or teacher for an idea
5. Use
any feature available to you
6. You
are allowed to talk quietly about the task at hand
7. Be
creative
The second concept map was assigned to students in class 7-2
on the topic: ‘What does the American Flag mean?’. These students used Inspiration to create
their concept maps. The students in
class 7-1 used paper and pen for the same topic. The students are arranged in the same
grouping for both learning mediums. The
classes received the following directions:
1. Work
together to create a concept map on the following topic: ‘What does the
American Flag mean?’
2. Use
any material you like on the topic
3. Do
not worry about wrong information or spelling
4. Do
not ask any group or teacher for an idea
5. Use
any feature available to you
6. You
are allowed to talk quietly about the task at hand
7. Be
creative
To eliminate topic bias, I have given both classes the same
topics and alternated the learning medium as described above. To eliminate student bias, I have maintained
the same student grouping throughout all aspects of the project. To eliminate grading bias, I have given the scoring
matrix and concept maps to an unrelated person for grading. The grader was a third year college student
who is studying education and uses concept maps in her classroom experiences
and her studies. To eliminate time bias,
I have set a time limit of 35 minutes for each session.
I will begin
with some definitions:
Connections: The
branches between points.
Major points:
Points that consist of concepts or main ideas.
Minor points:
Descriptive points which branch from major points.
The quantitative
variables for concepts map testing are:
·
The number of connections
·
The number of major points
·
The number of minor points
The qualitative
variables for concepts map testing are:
·
Quality of the position in which ideas are
grouped
·
Quality of answers (testing conceptual thinking)
·
Score using Nancy Fichtman Dana’s Concept Map
Scoring Rubric
Nancy
Fichtman Dana’s Concept Map Scoring Rubric:
Level
4
A
level 4-concept map is exciting (and perhaps even inspiring!) to examine. A level 4-concept map accurately conveys to
the instructor an original but viable understanding of what the student knows
about the topic and what information is known concerning the topic. The map contains concepts that emanate from a
variety of sources including: class sessions, textbook and other reading, unit
preparation and personal thoughts and experiences. The map should read in such a way that the
viewer can easily tell the difference between major and minor points and can
easily follow the connections made.
Connections that are made must be necessary and must be made with care -
there must be evident reason for making any connections. There is evidence that the concept map was
well planned. The map represents considerable
effort, learning, growth and reflection.
Level
3
A
level 3-concept map is satisfactory, but lacks the creativity and evidence of
personal growth and reflection apparent in a level 4-concept map. There is evidence that the student has spent
quality time working on the project, but more personal growth and reflection is
needed to come to a richer understanding of what it means to learn the
topic. The map contains concepts that
emanate from a variety of sources including class sessions, textbook and other
reading, unit preparation and personal thoughts and experiences. As with a level 4-concept map, the viewer
should be able to distinguish between major and minor ideas as well as follow
and comprehend all connections. There is
a lack of connection between the format and basic ideas put forth by the map’s
creators. The map represents
considerable effort.
Level
2
A
level 2-concept map demonstrates an understanding of material presented
throughout the unit but is limited in the number of concepts presented or is
too great in the number of concepts presented and therefore the connections
made between these concepts are superficial and difficult to follow. The map is dominated mainly by concepts
emanating from one or two sources only (class sessions or text) and the map
creators mainly rely on a pre-established organization of ideas for presenting
the concept map (for example, the map may be presented in a creative format,
but there is a lack of connection between the format and the basic idea put
forth by the map’s creators.) Portions
of the map may not represent a personal grounded understanding of the
topic. It is clear that more personal
growth and reflection is needed to come to a richer understanding of the topic.
Level
1
A
level 1-concept map shows a lack of preparation, planning and depth. Major concepts may be lacking, and/or there
is no apparent underlying theme or rationale for connections made between
concepts. It is clear that the student
had put little or no effort into the concept map creation.
Please
see appendix for examples of students’ work that demonstrates each of these
four levels.
It is important
to note:
20
computer-based concept maps were tested.
20 paper-based
concept maps were tested.
For medium,
‘Computer’ signifies that the map was computer-based. ‘Paper’ signifies that the map was paper-based.
For topic,
‘Flag’ signifies that the map was developed for the ‘What does the American
Flag mean?’ topic. ‘Government’
signifies the ‘Issues that the U.S. Government faced during the 1780’s and
1790’s’ topic.
The chart below depicts the
quantitative scoring results of the computer-based concept maps in the study:
For the computer-based concept map test, with regard to the
quantitative scoring, the average score on the number of connections was
3.35. The average score on the number of
major points was 3.5. The average score
on the number of minor points was 2.85.
The average of the average quantitative scores on the computer-based
concept maps is: 3.23.
The chart below depicts the qualitative scoring results of the computer-based
concept maps in the study:
For the computer-based concept map test, with regard to the
qualitative scoring, the average score on the quality of positioning was
2.95. The average score on the quality
of answers was 3.2. The average score
using Nancy Fichtman Dana’s Concept Map Scoring Rubric was 3.1. The average of the average qualitative scores
on the computer-based concept maps is slightly lower than the quantitative
results: 3.08.
The chart below depicts the quantitative scoring results of
the paper-based concept maps in the study:
For the paper-based concept map test, with regard to
quantitative scoring, the average score on the number of connections was
2.7. The average score on the number of
major points was 3.1. The average score
on the number of minor points was 2.3.
The average of the average quantitative scores on the paper-based
concept maps is: 2.7.
The chart below depicts the qualitative scoring results of
the paper-based concept maps in the study:
For the paper-based concept map test, with regard to
qualitative scoring, the average score on the quality of positioning was
2.6. The average score on the quality of
answers was 2.5. The average score using
Nancy Fichtman Dana’s Concept Map Scoring Rubric was 2.6. The average of the average qualitative scores
on the paper-based concept map is slightly lower than the quantitative scores
for paper-based: 2.57.
Under quantitative measures, the computer-based concept maps
scored 3.23 while the paper-based scored 2.7.
This is a difference or 0.53 or 13.33% (0.53/4 since the scores are
standardized out of a possible high score of 4). This implies that computer-based learning is
more effective than paper-based.
There was a 0.65 difference, or 16.25%, (again since the
scores are standardized out of a possible high score of 4, we can divide by 4
to see the percent of difference) between the average scores on the number of
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX:XXXXXXXXXXXXXXXXXXXXXXXXX
difference of 0.4, or 10%, on the number of major points
variable. There was a 0.55, or 13.75%
difference on the number of minor points
variable. These three factors can be
contributed to two things. The first
factor is time. Many students find it
faster to type rather than to print. The
second factor is space. There are
limitations to the amount of space a paper allows for printing,
however the computer will automatically fit the concept map to a standard
page. A student may start a map on paper
and run out of space quickly due to poor planning or large print.
Under qualitative measures, the computer-based concept maps
scored 3.08 while the paper-based scored 2.57.
This is a difference or 0.52 or 12.92%.
This also implies that computer-based learning is more effective than
paper-based.
There was a 0.35, or 8.75%, difference in the average scores
on the quality of positioning. I
expected this variable to have a greater difference, since the software will
allow students to re-arrange their placement.
Although this is time consuming, it is more efficient than erasing and
re-writing in paper and pen.
There was a 0.7, or 17.5%, difference in the average scores
on the quality of answers and is the most significant difference. This also surprises me and I can’t explain
the variance. The computer-based concept
maps were conducted last and this may have contributed to the quality of
answers. However, students have practice
using paper-based concept maps throughout the school year, so it shouldn’t have
an effect.
There was a 0.5, or 12.5%, difference in the average of
scores using Nancy Fichtman Dana’s Concept Map Scoring Rubric. This does not come as a surprise, since it
reflects the average of all scores.
Further, I have gathered the scores sorted by topic and the results are given
in the charts below. The first chart
displays the quantitative measures for the ‘What does the American Flag mean?’
topic concept map test.
For the ‘What does the American Flag mean?’ topic concept
mapping test, with regard to quantitative scoring, the average score on the
number of connections was 3.05. The
average score on the number of major points was 3.3. The average score on the number of minor
points was 2.5. The average of the
average quantitative scores on the ‘What does the American Flag mean?’ topic
concept mapping test is: 2.95.
The chart below displays the qualitative measures for the
‘What does the American Flag mean?’ topic concept map test.
For the ‘What does the American Flag mean?’ topic concept map
test, with regard to qualitative scoring, the average score on the quality of
positioning was 2.75. The average score
on the quality of answers was 2.7. The
average score using Nancy Fichtman Dana’s Concept Map Scoring Rubric was
2.75. The average of the average
qualitative scores on the ‘What does the American Flag mean?’ topic concept map
is: 2.73.
The chart below displays the quantitative measures for the
‘Issues that the U.S. Government faced during the 1780’s and 1790’s’ topic
concept map test.
For the ‘Issues that the U.S. Government faced during the
1780’s and 1790’s’ topic concept map test, with regard to quantitative scoring,
the average score on the number of connections was 3. The average score on the number of major
points was 3.3. The average score on the
number of minor points was 2.65. The
average of the average quantitative scores for ‘Issues that the U.S. Government
faced during the 1780’s and 1790’s’ topic concept map is: 2.98.
The chart below displays the qualitative measures for the
‘Issues that the U.S. Government faced during the 1780’s and 1790’s’ topic
concept map test.
For the ‘Issues that the U.S. Government faced during the 1780’s
and 1790’s’ topic concept map test, with regard to qualitative scoring, the
average score on the quality of positioning was 2.8. The average score on the quality of answers
was 3. The average score using Nancy Fichtman Dana’s
Concept Map Scoring Rubric was 2.95. The
average of the average qualitative scores for ‘Issues that the U.S. Government
faced during the 1780’s and 1790’s’ topic concept map is: 2.92.
Under quantitative measures, the
‘What does the American Flag mean?’ topic scored 2.95 while the ‘Issues that
the U.S. Government faced during the 1780’s and 1790’s’ topic scored 2.98. This is a difference of 0.03 or 0.83%. This implies that there was virtually no
difference between topics, though it wouldn’t have mattered if there was, since
both classes experienced each topic.
Under qualitative measures, the ‘What does the American Flag
mean?’ topic scored 2.73 while the ‘Issues that the U.S. Government faced during
the 1780’s and 1790’s’ topic scored 2.92.
This is a difference of 0.18 or 4.58%.
This implies that though a slightly greater difference, there was still
virtually no difference between topics, using qualitative measures, though
again it wouldn’t have mattered if there was, since both classes experienced
each topic.
Please
see appendix for statistical results based on topic variance.
We’ve drawn conclusions based on the data, but the
next step is to determine whether or not the model has statistical
significance. If the model is
statistically significant, we can broaden our conclusion that computer-based
concept mapping outperforms paper-based concept mapping to an overall
generalization. If the model is good, we
would expect that concept mapping in various schools is better taught on the
computer than on paper.
We combined the quantitative measures with the qualitative measures (as
depicted in the chart below) and used a statistical software package (SPSS
version 10.0), to run multiple linear regression. This will determine the model’s statistical
significance.
Null Hypothesis: This is not a good model.
Alternative Hypothesis: Reject the null hypothesis (the model
has statistical significance).
N = 40
Dependent Variable: Computer-based concept mapping
software
Independent
Variables:
X1 = Number of
Connections
X2 = Number of Major
Points
X3 = Number of Minor
Points
X4 = Quality of
Positioning
X5 = Quality of Answers
X6 = Dana’s Rubric
R Square
is a measure that can help us correlate the variance in results with the
independent variables. R
Square is adjusted (adjusted R
Square) to take into account the size of the
sample. If the sample size is large, R
Square will be close to adjusted R
Square, however if the sample size is small, R
Square will differ from adjusted R
Square.
Either way, a statistician should use the measure of adjusted R
Square to explain variance. In our case, the adjusted R
Square illustrates that the independent variables
that we used (the scoring measures) can explain 13.2% of the variance in
concept mapping medium (paper or computer).
This is a low proportion and is evidence that the model is not
statistically significant. Additionally,
the difference between R Square
and adjusted R Square is
evidence that our sample size was too small.
The ANOVA table above depicts a
p-value of 0.095. At a confidence
interval of 95%, the p-value indicates that we cannot reject the null
hypothesis (the slope is close to or
equal to zero). Thus the
interpretation is that this case study lacks statistical significance at the
95% confidence level. However, we can
say with 90% certainty that the model is statistically significant. The p-value is below 0.10 (it is 0.095), so
at a confidence interval of 90% this case study does hold statistical
significance.
Note: the variable labeled ‘Overall’ is Dana’s Rubric measure.
According to the coefficients data,
the regression model indicates an unstandardized value for a concept map of
-0.174 if the scoring variables were at zero.
However, logic dictates that a concept map score can never be
negative. Therefore, a more appropriate
regression is one that forces the intercept term (B0) to be
zero. You’ll notice that the
standardized value of the intercept term (B0) depicts the results
when the intercept term is zero.
The low p-value for X1,
Number of Connections (0.038), indicates that while the model as a whole is not
statistically significant at 95%, Number of Connections is a good measure for
correlation. Additionally, X5,
Quality of Answers, is a good measure for correlation as demonstrated by its
low p-value (0.043).
The other
four variables are not good measures. X2,
Number of Major Points, has a p-value of 0.11, which is slightly out of
range for a 95% level of confidence. X3,
Number of Minor Points, has a p-value of 0.235, which is out of range for a 95%
confidence. X4, Quality of
Positioning, has a p-value of 0.28, which is also out of range for a 95%
confidence. X6, Dana’s Rubric
has the highest p-value (0.492), making it the worst measure for
correlation.
According to the residuals
statistics, the errors are slightly right-skewed but are very close to being
evenly distributed, illustrating that the model is stable.
To summarize the statistical data, using a 95% confidence
interval there is statistical significance for X1, the Number of
Connections variable, because significance is 0.038 (less than 0.05). There is also statistical significance with
95% confidence for X5, the Quality of Answers variable, because
significance is 0.043 (less than 0.05)
For the model overall, using a 95% confidence interval we
cannot reject the null hypothesis. Thus
the interpretation is that with 95% confidence this case study lacks
statistical significance. Adjusted R
Square is very close to 0 and on the ANOVA table, the p-value is close to but greater than 0.05. However, we can conclude with 90% confidence
that computer-based concept mapping is superior to paper-based. We cannot say at a 95% level of confidence
that the model adds value. That doesn't
mean that the model doesn't have value, only that we cannot reject the null
hypothesis at 95%. Since there is some
evidence it does add value (and there does not appear to be any evidence that
it detracts value), and it would seem to be that it does no harm to use the
computer versus paper; there is potential good and no potential harm. Additionally, use of the computer adds a
valuable skill independent of the purpose of the exercise.
The sample, and its size, of a study
should be a function of the variation in the population parameters, as well as
the precision needed by the researcher.
In our study, we did not have the option of choosing a sample that would
be reflective of the population as a whole.
Additionally, the students in the study were not chosen in a simple
random fashion. Pairing up of students
into groups was not conducted at random either.
Students were asked to work with the peer who sat next to them. The students seating arrangement was decided
upon by their primary teacher. Both
teachers had seated the students according to their height order unless a behavioral
problem arose, at which time seating arrangements were changed to curb the
behavior.
This school’s demographic makeup is not representative of the
United States’
demographic makeup, particularly in terms of: class, race, culture, lifestyle,
and religion. The school is typical of
many urban and suburban areas in the U.S.
in the way that populations tend to be voluntarily segregated based on culture,
religion, race, lifestyle, and class.
However, if we were interested in generalizing the results of this study
for the U.S. as
a whole, the sample makeup should be representative of the general population
(in terms of diversity following the same ratios as the population).
Another limitation to this study was the small sample size
(N).
Some principles that influence sample size include:
·
The greater the dispersion or variance within
the population, the larger the sample must be to provide estimation precision.
·
The greater the desired precision of the
estimate, the larger the sample must be.
·
The narrower the interval range, the larger
the sample must be.
·
The higher the confidence level in the
estimate, the larger the sample must be.
·
The greater the number of subgroups of
interest within a sample, the greater the sample must be, as each subgroup must
meet minimum sample size requirements.
·
If the calculated sample size exceeds 5
percent of the population, sample size may be reduced without sacrificing
precision. (Cooper and Schindler,
172).
In
particular, three of these principles directly influence our study. We desire a 95% confidence interval, which
implies that the sample should be large.
In addition, the interval range of our scoring method (1-4) is very
narrow. This also implies that the
sample size should have been large.
One
factor, which may or may not have had an effect on the performance of the
students in the sample, is the sudden death of their math teacher (one of the
primary 8th grade teachers).
She passed away approximately 2 months before the study was
conducted. She was widely known and
respected among the student body.
Initially, I had planned on conducting my study on the 8th
grade. However, after Mrs. Germano
passed away I felt that a study on those students would be biased since one
class would have been more affected than the other. Though the seventh grade was negatively affected
by her passing, as was the entire school, I do not believe that either one of
the 7th grade classes were more affected by the tragedy.
In
conclusion, in my research study computer-based concept maps have proven better
than paper-based. I found the students
to be more involved when using Inspiration software. They were more excited to show me their work,
and in general the computer-based concept maps were: neater, more thorough, and
scored higher on all of the measures I used.
Let’s examine a few groups in
particular. We’ll look at the
quantitative measures, since they are objective (see
the chart below).
It’s important to
note that 11 groups benefited from the computer, while 5 performed better on
paper. Four groups scored the same on
both mediums. It is interesting to see
that the groups’ that performed best on the computer tended to score
significantly higher on the computer, whereas for those that tended to perform
best on paper theirs scores did not improve as drastically. This proves that there is no ‘best’ teaching
style. A multiple learning style
environment benefits the most students.
Anderson-Inman, Lynne and Leslie Ditson, “Computer-Based
Concept Mapping: a tool
for
negotiating meaning” Learning and Leading with Technology 26 no8 6-13
May '99.
Brunner, Cornellia and William Tally. The New Media Literacy Handbook An
Educator’s Guide to Bringing New
Media Into The Classroom. Doubleday, New
York, 1999.
Carvin, Andy. “The E-Rate in America:
A Tale of Four Cities”. The Benton
Foundation,
Feb 2002.
Cooper, Donald R and Pamela Schindler. Business Research
Methods Seventh Edition.
McGraw-Hill
Higher Education, New York, 2001.
Daley, Barbara J., Christine R. Shaw, Toni Balistrieri, Kate
Glasenapp and Linda
Piacentine. “Concept Maps: A Strategy to Teach and
Evaluate Critical
Thinking”. Journal of Nursing Education 38 no1 42-7 Ja '99.
Herl, Howard E. and Eva L. Baker. “Construct Validation of an Approach to
Modeling
Cognitive Structure
of U.S. History Knowledge”.
The Journal of Educational
Research Washington, DC v89 p206-18.
Plotnick, Eric. “A
Graphical System for Understanding the Relationship between
Concepts”. Teacher Librarian 28 no4 42-4 Ap 2001.
Romance, Nancy R. and Michael R. Vitale. “Concept Mapping as a Tool for Learning:
Broadening the
Framework for Student-Centered Instruction”. College Teaching
47 no2 74-9 Spr '99
Stanley, William, Critical Issues In
Social Studies Research for the 21st Century.
Information Age Publishing, Connecticut,
2001.
Steinberg, Shirley R. and Joe L.
Kincheloe. Students As Researchers Creating
Classrooms
That Matter. Falmer Press
Teachers’ Library, London, 1998.
http://www.ericit.org/digests/EDO-IR-1997-05.shtml
www.inspiration.com
http://www.inspiration.com/vlearning/index.cfm
www.palm.com
Multiple Regression performed on Topic
(‘What does
the American Flag mean?’ topic verses ‘Issues that the U.S.
Government faced during the 1780’s and 1790’s’ topic)
Null Hypothesis: This is not a good model.
Alternative Hypothesis: Reject the null hypothesis (the model
has statistical significance).
N = 40
Dependent
Variable: Topic for Concept
Map
Independent
Variables:
X1 = Number of
Connections
X2 = Number of Major
Points
X3 = Number of Minor
Points
X4 = Quality of
Positioning
X5 = Quality of Answers
X6 = Dana’s Rubric
In
this scenario, rejecting the null hypothesis would tell us that there is a significance to the difference with regard to concept maps
performed on one topic verses the other.
If we cannot reject the null hypothesis, we can conclude that there is
no statistical significance to the difference between concept map performance for one topic verses the other. In essence, we hope that this is not a good
model.
In this case, adjusted R
Square is negative. It is very close to zero (-0.088), indicating
that the independent variables that we used (the scoring measures) cannot
explain the variance in topic. This is
evidence that the model is not statistically significant.
The ANOVA table above depicts a p-value of
.823. At a confidence interval of 95%,
the p-value indicates that we cannot reject the null hypothesis (the slope is equal to zero). The p-value indicates that this model is very
far from being statistically significant.
Thus the interpretation is that this is not a good model. We can conclude that there is no statistical
significance to the difference between concept map performance
for one topic verses the other.
