Problem Based Learning in a Pathophysiology On-line Review System
Peter Carafano*
Health Science Department, Florida State University Schools, Tallahassee, Florida, USA
*Corresponding author:Peter Carafano, HealthScience Department, Florida State University Schools, Tallahassee, Florida, USA.Tel: +18502453700; E-Mail: pcc03@fsu.edu
Received Date:11May, 2017; Accepted Date: 03 June, 2017; Published Date:12
June, 2017
Citation: Carafano P (2017) Problem Based Learning in a Pathophysiology On-line Review System. Educ Res Appl 2017: ERCA-119. DOI: 10.29011/2575-7032/100019
1. Abstract
This study examines the effect of an on-line problem based learning system on high school students in a health science program. The learning system focuses on critical thinking skills as they relate to determining the diagnosis of a disease based on physical assessment and the understanding of pathophysiology. The study findings suggest that the on-line review system significantly improved the student’s ability to determine the correct diagnosis from information presented in a scenario based problem format. The study was implemented after a full and comprehensive review and approval by the Human Subjects Committee at Florida State University.
2.
Keywords:Computer
Supported Learning; Critical Thinking; Health Science; Pathophysiology and Diagnosis.
1. Introduction
Health science education is commonly becoming a part of the various programs offered to high school students throughout the United States. These programs are developed for students interested in entering the medical profession and obtaining state certification in entry level occupations before graduation.
The difficulty in these programs is the necessity to train adolescents to function in an atypical environment and operate at an adult level. Unlike the typical high school setting, these students must learn to operate within a system that requires mature levels of critical thinking to function safely.
Yet students frequently become passive in the process of receiving knowledge, especially in light of the advances in technological access. It is apparent that students need to learn to “Develop and effectively apply critical thinking skills to their academic studies, to the complex problems that they will face, and to the critical choices they will be forced to make” [1].
Therefore, in this study we examined the effect of an on-line problem based learning system on high school students in a health science program. The major research questions are:
·
What
is the learning effectiveness of an on-line problem focused pathophysiology
review system?
·
Does
the on-line problem based pathophysiology review system improve student’s
critical thinking in the area of medical diagnosis?
2. Literature Review
Researchers
that focus on the area of critical thinking have identified that frequently
this skill is not very well developed in both children and adults. In the field
of psychology, researchers have concluded that a significant amount of adults
have difficulty with critical thinking [2-4].
The ability to effectively utilize critical thinking is essential in medicine to meet patient needs, identify potential problems, develop proper interventions and in many cases, develop alternative therapies. Health care providers must be able to provide care based on an understanding of pathophysiology behind the problem being addressed[5].
To facilitate this process, teachers need to utilize diverse methods for instruction and expose students to various methodologies[6]. When evaluating the best approach to teaching critical thinking research suggests that educators should utilize a mixed approach that integrates various strategies into standard instructional content [7].
One such area involves the use of the integration of explicit instruction, a process whereby the learner receives clear and precise explanations regarding the necessary skills and information they are required to learn [7,8]. In addition, explicit to instruction is another key component to successfully teaching critical thinking skills is the role that background knowledge represents in the process. Researchers have concluded that this is an essential component to the process[9]. Students must have a foundation in this area so that they have the necessary tools to solve complex problems [4]. Therefore, any instructional system must provide for the integration of background knowledge to be successful.
As part of the critical thinking learning process, a method of assessment tasks must be included. These tasks should involve the application of authentic real-world problems [2,10]. The basis for theses assessments should be structured and include simulations that can approximate conditions that could be encountered in the real-world [11].
Researchers have demonstrated that technology and web based instruction can support and enhance traditional classroom instruction. That computer based instruction can be effective in improving learning when supported with traditional instructional methods[12,13].
3. Method
This study used a quantitative approach to evaluate the effect of problem based learning in on-line review system. This system was implemented to augment the normal instruction given to high school health science students in the area of the pathophysiology of disease. Specifically, the ability to diagnosis these illnesses when presented with a problem based scenario in which specific signs and symptoms are provided.
The online study system was accessed by the research students using chrome books on a dedicated web site that only they had access to. The study system was made up of two parts, an explicit instructional unit and a scenario based review unit.
The explicit instructional review unit was made up of three separate lessons covering cardio-pulmonary, abdominal and neurological diseases. Each disease was summarized in a one page format (Appendix 1) which included a graphic representation, a one paragraph explanation of the physiology of the diseases process and a list of the common symptoms.
The scenario based review unit (Appendix 2) was developed using a PowerPoint based learning tool. Students would review various scenarios after each explicit instructional unit, which included different situations, complaints and assessment results. After they reviewed the given information they were provided a list of possible options and were instructed to attempt to determine the possible diagnosis. Once an option was selected the student was then shown the correct answer, the rationale and identifiers in the scenario that supported the correctdiagnosis.
3.1. Participants
The study consisted of thirty-six 11thgrade students from a Health Science II course at a local high school. Of the thirty-six students involved in the study 22.2 % were male and 77.8 % were female. Participants were randomly assigned to two groups. The control group (n=17) were provided standardized instruction in pathophysiology and diagnosis. The research group (n=19) were provided with the on- line scenario based study system in addition to the standardizedinstruction.
3.2. Procedure
The study lasted 12 weeks. In the first week, all study participants received a pre- test which used a scenario based format. In the pre-test, the student was provided written scenarios in which they had to evaluate the signs and symptoms and render a diagnosis from a group of possibleoptions.
All
participants were then provided equivalent instruction over the following ten
weeks which was divided into three separate units. During each unit, the
students assigned to the research group were instructed to use the on-line
system to review the diseases covered in lecture. To ensure the students
reviewed the material they were required to copy the written pathophysiology
for each disease and list of symptoms from the explicit instructional unit into
a dedicated composition book separate from their classroom notes.
Data was collected using quantitative knowledge tests. Specifically, at the completion of the first two unit’s two different assessment tests were administered. The first test, designated as the short answer test, provided the student with ten diagnosis that were randomly selected from the list of diseases that they had studied in class and were covered by the review program. These tests were specific to the unit that the instructor had just completed teaching and was administered within 1-2 days. The student was required during the test to write from memory the basic pathophysiology of the disease and at least three common signs or symptoms (factual knowledge test).
The second assessment test used a scenario based format similar to what was used in the pre-test; this was designated as the scenario test. In this test, the students were given five scenarios that encompassed the common signs or symptoms of specific diseases they had learned in class and that was also covered by the review system. The student was then required to read the scenario, evaluate the signs and symptoms and then using critical thinking skills identify the diagnosis from memory, no options were provided (Problem solving test). The assessment test was administered 1-2 days after the short answer test. In the last week, the students were given the post-test which used the same instructional format and questions used in the pre-test. In the post-test, the students were provided an alphabetical list of possible diagnosis that was covered in the course as well as the review program from which to pickfrom.
Test items were extracted directly from the explicit instructional units by expert teachers not associated with the school. The test questions were validated through prior administration to an advanced Health Science class of fifteen students not involved in the study. Test question validation was implemented six months prior to the study.
3.4. Findings
Initially
a one way MANOVA test was conducted to examine impact of an on-line problem
focused pathophysiology review system on student’s critical thinking in the
area of medical diagnosis. When we compare the mean scores of the control group
versus the research group in the Descriptive Table(Table
1) for the scenario, short answer, and post-test scores we do see a
difference in the mean scores. On average the Research group means score was
48% higher than that of the Control group for all tests. The results of the
MANOVA analysis showed a significant difference between the research group and
the control group in post testing where F(1,34) = 78.311, p< 0.001.
A
Levene’s Test for Homogeneity of Variances (Table 3)
was conducted to ensure that the variability of scores for each group was
similar where (sig. > 0.05), in all cases the results were not significant.
The strength of the variation for the short answer tests, scenarios tests and
the post-test was supported by the values reported for Partial Eta Squared (Table 2) which all show a large effect size (eta2>0.14). When we look at the Between Subject
Factors (Table 2) we see that there is a
statistically significant effect (sig.<0.05) between both groups for short
answer, scenario based and the post- test.
After evaluation of the results an ANCOVA analysis was conducted using the pre-test as a covariate and the post-test as the dependent variable. The intent was to determine if there was an overall statistically difference in the post -test scores between the two groups once their means had been adjusted for the pre-test scores. In the Tests of Between Subjects(Table 4) we see that there is a statistical significant difference between groups when adjusted for the covariate (sig. < 0.05). This is better understood by the difference between the means for both in the Descriptive Statistics Table (Table 5) when compared to the adjusted means in the Estimates Table(Table 6). The difference between the pre-and post-test can be visually highlighted by the box plot graphs based on the adjusted means (Graph 1 & 2).
4. Conclusion and Discussion
The on-line problem focused pathophysiology review system did have a positive impact on the student’s learning within the Research group. This was determined by the significantly higher mean on the scenario, short answer, and post-test scores as compared to the Control group. In regard to critical thinking, the Research group demonstrated significantly higher mean scores on the scenario based testing as compared to the Control group. It is these scenarios based tests that demonstrate not only the understanding of pathophysiology but the ability to think critically in order to determine a medical diagnosis from the evidence or information provided.
As we look at prior research discussed in the literature review, the results of this study confirm the difficulty students can have with critical thinking as it relates to solving medical based problems. The introduction of this learning system also substantiates the need to use various methodologies and strategies of instruction to teach critical thinking skills, especially in the area of medical based instruction. The importance and success of explicit instruction is also supported by the results of this study based on student performance in both the factual knowledge and problem-solvingtests.
This study also supports our present understanding of the positive impact technologybasedlearninghasonimprovingcriticalthinkingskills.Especiallywhen used in a system such as this which includes the application of solving real world problems in the process.
In the field of health care the ability to think critically is of paramount importance in order to function effectively and safely in the area of patient care. The goal of training high school students to competently work in health care after graduation is a daunting responsibility. To meet these responsibility educators must use multiple resources to help accomplish thisgoal.
Appendix 1: Explicit
Instructional Review.
Appendix
2: The Scenario Based Review Unit
Graph 1:Pre -testandGraph2:Post -test.
Dependent Variable
|
Group |
Mean |
Std. Error |
95% Confidence Interval |
|
Lower Bound
|
Upper Bound |
||||
Unit 1 Short Answer |
Control |
37.706 |
4.843 |
27.864 |
47.547 |
Research |
71.263 |
4.581 |
61.954 |
80.572 |
|
Unit 1 Scenario |
Control |
22.059 |
7.242 |
7.341 |
36.776 |
Research |
63.158 |
6.85 |
49.237 |
77.079 |
|
Unit 2 Short Answer |
Control |
52.235 |
4.539 |
43.012 |
61.459 |
Research |
77.789 |
4.293 |
69.065 |
86.514 |
|
Unit 2 Scenario |
Control |
38.824 |
5.801 |
27.035 |
50.612 |
Research |
85.263 |
5.487 |
74.112 |
96.414 |
|
Post-test |
Control |
39.118 |
3.918 |
31.156 |
47.08 |
Research |
86.842 |
3.706 |
79.311 |
94.374 |
Table 1: Control Group Versus the Research Group (Descriptive Table).
Source
|
Dependent Variable |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Partial Eta Squared |
Group |
Unit 1 Short Answer |
10103.536 |
1 |
10103.536 |
25.342 |
0 |
0.427 |
Unit 1 Scenario |
15155.283 |
1 |
15155.283 |
16.998 |
0 |
0.333 |
|
Unit 2 Short Answer |
5859.006 |
1 |
5859.006 |
16.731 |
0 |
0.33 |
|
Unit 2 Scenario |
19349.845 |
1 |
19349.845 |
33.825 |
0 |
0.499 |
|
Post test |
20435.348 |
1 |
20435.348 |
78.311 |
0 |
0.697 |
Table 2: Between Subject Factors.
|
F
|
df1 |
df2 |
Sig. |
Unit 1 Short Answer |
1.826 |
1 |
34 |
0.186 |
Unit 1 Scenario |
3.119 |
1 |
34 |
0.086 |
Unit 2 Short Answer |
1.492 |
1 |
34 |
0.23 |
Unit 2 Scenario |
1.751 |
1 |
34 |
0.195 |
Post test |
0.003 |
1 |
34 |
0.956 |
Table 3: Levene's Test Homogeneity of Variances.
Source
|
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Partial Eta Squared |
Corrected Model |
21285.860a |
2 |
10642.93 |
43.783 |
.000 |
0.726 |
Intercept |
10994.118 |
1 |
10994.118 |
45.228 |
.000 |
0.578 |
Pretest |
850.512 |
1 |
850.512 |
3.499 |
.070 |
0.096 |
Group |
17506.227 |
1 |
17506.227 |
72.017 |
0 |
0.686 |
Error |
8021.779 |
33 |
243.084 |
|
|
|
Total |
178175 |
36 |
|
|
|
|
Corrected Total |
29307.639 |
35 |
|
|
|
|
Dependent Variable:Post - test. R Squared = .726 (Adjusted R Squared =.710) |
Table 4:Tests of Between-Subjects Effects.
Group
|
Mean |
Std. Deviation |
N |
Control |
39.1176 |
16.79242 |
17 |
Research |
86.8421 |
15.56443 |
19 |
Total |
64.3056 |
28.93719 |
36 |
Dependent Variable:Post- test. |
Table 5: Descriptive Statistics.
Group
|
Mean |
Std. Error |
95% Confidence Interval |
|
Lower Bound |
Upper Bound |
|||
Control |
40.341a |
3.838 |
32.533 |
48.149 |
Research |
85.748a |
3.624 |
78.374 |
93.121 |
Dependent Variable: Post - test. a-Covariates appearing in the model are evaluated at the following values: Pre-test = 30.8889 |
Table 6: Estimates.
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