Critical Thinking, Self-Efficacy, and Self-Regulated Learning in University Students

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  • Self-efficacy is the cornerstone of the Social Cognitive Theory.
  • Talk about how we got subject, then talk about subjects.
  • For the online participant recruitment, invitations were sent to Benedictine University students enrolled in the Spring 2011 semester/quarter via e-mail. 3 separate e-mails were sent out between April 28 th and May 10 th of this year. As an incentive, $100 would be awarded via a random drawing. A written invitation for the online survey was also included in the In-Class survey packets. ** Show pink slip for online survey handed out in class
  • The online survey consisted of both the MSLQ survey, as Sarah just explained, and the Metacognitive Awareness Inventory survey, or MAI. The MAI is a 52 item self-report inventory tool that measures adults’ metacognitive awareness one’s “thinking about thinking” These statements are used to gauge knowledge of cognition & regulation of cognition .
  • Participants completed the online surveys via SurveyMonkey, a web-based survey service. Completed surveys were linked to Benedictine’s website (all information was kept confidential). Survey responses were entered into an Excel doc and then exported into IBM SPSS 19 to analyze the data.
  • To run the data analyses we used: Frequencies and Descriptives (to check for errors) Factor Analyses (to extract factors) Cronbach Alpha (for reliability) One Way ANOVAs (for analysis of variance) Independent t-tests (for comparing means) Pearson r (for correlations) … and we used these variables for the analyses
  • Self efficacy statements included: I believe I will receive an excellent grade in this class I’m certain I can understand the most difficult material presented in the readings for this course I’m confident I can understand the basic concepts taught in this course I’m confident I can understand the most complex material presented by the instructor in this course I’m confident I can do an excellent job on the assignments and tests in this course I expect to do well in this class I’m certain I can master the skills being taught in this class Considering the difficulty of this course, the teacher, and my skills, I think I will do well in this class Critical thinking : I often find myself questioning things I hear or read in this course to decide if I find them convincing When a theory, interpretation, or conclusion is presented in class or in the readings, I try to decide if there is good supporting evidence I treat the course material as a starting point and try to develop my own ideas about it I try to play around with ideas of my own related to what I am learning in the course Whenever I read or hear an assertion or conclusion in this class, I think about possible alternatives.
  • >.9 = Excellent .9->.8 = Good .8- >.7 = Acceptable
  • No significance for critical thinking state range verbally Sig for self eff = .029 which is less than .05, so use equal variance not assumed,  no significant difference (sig 2 tailed) = .567 Sig for critical think = .999, so equal variance is assumed  no significant difference (sig 2 tailed) = .494, t-value = .686, and df = 76.024, no significance b/t majors and critical thinking, mean diff = .14999
  • Self eff 23 and under (nutrition) N = 101 Mean = 5.9480 SD = .75462 24 and over N = 43, Mean = 5.8459, SD = 1.05498 Other 23 – N = 24, mean = 6.3646, SD = .13500 24 + N = 0
  • Self efficacy increased with every grade – address why no “f’s”
  • There is a significant relationship between self efficacy and nutrition majors (despite their tendency to report lower levels of self efficacy)
  • The ttest shows significance, hypothesis rejected. .011 less than .05, shows significance between critical thinking and course outcome
  • There is not a significant correlation between critical thinking and course grade
  • As already mentioned, the online survey consisted of both the MSLQ and the MAI questionnaire.
  • This graph depicts age and gender distribution for the online study. Out of 88 participants, 90% were female and 10% were male. Age is categorized into 2 groups: 23 yrs of age & under and 24 yrs of age and & over. Of these there were 63 females 23 yrs of age & under and 16 females 24 yrs of age & over. Males were all in the 23 and under category.
  • The ethnicity distribution was 67% white and 33% non-white.
  • The distribution by majors was 60% Education and 40% Nutrition.
  • We ran a PCA to determine the factors of the MSLQ online survey questions. As with the In-Class survey, the MSLQ separated into 2 factors: Critical Thinking and Expectancy, but only for the Nutrition and Education majors. Because there was a significant mismatch between all other majors, only the results from Nutrition and Education courses were retained
  • We ran a PCA to determine the factors of the MAI online survey questions. The MAI (Metacognitive Awareness Inventory) consists of 2 broad categories containing multiple factors Knowledge of cognition Regulation of cognition Declarative knowledge Planning/goal setting Procedural knowledge Information management Conditional knowledge Monitoring Debugging Evaluation Because there was a significant mismatch between ‘all majors’ and the MAI PCA results originally reported by the researchers who developed the scale, Shraw & Dennison, the factors could not be used in the data analyses. There was also a definite mismatch between Nutrition and Education and all the other majors, which suggests there are different SRL skills utilized by other groups.
  • A Cronbach Alpha was run to determine internal consistency between the 52 survey questions of the MAI. The top table demonstrates an ‘excellent’ internal consistency D/T it being > .9. The bottom table is a sample representation of the 3 highest (in yellow) and 3 lowest (in blue) of the MAI means. The scores in yellow demonstrate a ‘good’ internal consistency D/T their being > 8. The scores in blue demonstrate ‘ questionable’ internal consistency D/T their being > 6. Cronbach's alpha is the most common measure of internal consistency ("reliability"). It is most commonly used when you have multiple Likert questions in a survey/questionnaire that form a scale and you wish to determine if the scale is reliable. Note: George and Mallery (2003) provide the following rules of thumb when interpreting Cronbach alpha: “_ > .9 – Excellent , _ > .8 – Good, _ > .7 – Acceptable, _ > .6 – Questionable, _ > .5 – Poor, and _ < .5 – Unacceptable” (p. 231). George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Boston: Allyn & Bacon.
  • A Cronbach Alpha was also run to determine internal consistency between critical thinking, self-efficacy, the MSLQ and MAI surveys. Because each factor is > .9, they all demonstrate an excellent internal consistency. Cronbach's alpha is the most common measure of internal consistency ("reliability"). It is most commonly used when you have multiple Likert questions in a survey/questionnaire that form a scale and you wish to determine if the scale is reliable. Item Total Statistics table - good table for reliability, supports inclusion of all items - shows elimination of any item will decrease the reliability. All 4 variables have great reliability. Note: George and Mallery (2003) provide the following rules of thumb when interpreting Cronbach alpha: “_ > .9 – Excellent, _ > .8 – Good, _ > .7 – Acceptable, _ > .6 – Questionable, _ > .5 – Poor, and _ < .5 – Unacceptable” (p. 231). While increasing the value of alpha is partially dependent upon the number of items in the scale, it should be noted that this has diminishing returns. It should also be noted that an alpha of .8 is probably a reasonable goal. It should also be noted that while a high value for Cronbach’s alpha indicates good internal consistency of the items in the scale , it does not mean that the scale is unidimensional. Factor analysis is a method to determine the dimensionality of a scale George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Boston: Allyn & Bacon.
  • As you can see in your handout booklet, there are quite a few slides of all of the hypotheses tested for the online survey. There are three broad categories within these hypotheses: Self-efficacy, Critical Thinking and MAI/SRL In the interest of time and to better describe the results, instead of going through each slide separately, I will use comparison tables, one for each category. These three tables are not in your handout, but the information in each one has been taken from the slides that are in your handout booklet. I will begin with the Null H0s 8 thru 12b for self-efficacy.
  • After determining the internal consistencies, the hypotheses were then tested. I began with a t-test to prove there in no difference between majors in self-efficacy. Because the p value is < 0.05, it demonstrates there is a sig. difference between majors and self-efficacy . The null hypothesis is rejected. T-test The sig (2-tailed) is less than .05 (.036) which demonstrates there is a significant difference between majors and self-efficacy. The null hypothesis is rejected.
  • A One Way ANOVA was then run to test the relationship between academic year and self-efficacy in nutrition majors. There is an inverse relationship between the f value and the p value. The p value is greater than 0.05, which shows there is no sig. difference in self-efficacy between the academic year groups.
  • One Way ANOVA There is a definite relationship between academic year and self-efficacy in education majors. There is an inverse relationship between the f value and the p value. In this case, the f value is large and the p value is small. Because the p value is < 0.05, there is a sig. difference in self-efficacy between the academic year groups. The null hypothesis is rejected, therefore the f value is further from 1.0.
  • One Way ANOVA There is no relationship between self-efficacy and age in nutrition majors. The null hypothesis is accepted. There is an inverse relationship between the f value and the p value. The p value is greater than 0.05, which shows there is no sig. difference in self-efficacy between the age groups of nutrition majors. The null hypothesis is accepted, therefore the f value is closer to 1.0.
  • ANOVA There is no relationship between self-efficacy and age in education Majors. The null hypothesis is accepted. There is an inverse relationship between the f value and the p value. The p value is greater than 0.05, which shows there is no sig. difference in self-efficacy between the age groups of education majors. The null hypothesis is accepted, therefore the f value is closer to 1.0.
  • T-test (split file) The sig (2-tailed) is greater than .05 (.130) so there is no significant difference between self-efficacy and ethnicities in nutrition majors. The null hypothesis is accepted.
  • T-test (split file) The sig (2-tailed) is greater than .05 (.102) so there is no significant difference between self-efficacy and ethnicities in education majors. The null hypothesis is accepted.
  • Pearson r There is no significant relationship between self-efficacy and cumulative GPA in nutrition majors. The null hypothesis is accepted.
  • Pearson r There is a defined relationship between GPA and self-efficacy in education majors. The higher the self-efficacy, the higher the GPA and vice versa. The null hypothesis is rejected.
  • As you can see, there was a significant difference between self-efficacy and majors, at .036, so the null hypothesis was rejected. Between self-efficacy and the academic year, there was no sig. difference for nutrition majors, so the null H0 was accepted, but for the education majors, there was a sig. difference, at .014 in self-efficacy. With self-efficacy and the age categories and ethnicity groups, there was no sig. difference in both nutrition and education majors, so these 4 null h0s were accepted. But with self-efficacy and cumulative GPA, whereas there was no sig. difference in nutrition majors, causing the acceptance of the null H0, there was a sig. difference in the education majors causing the rejection of the null H0.
  • These are the null hypotheses 13 thru 17b for critical thinking
  • T-test The sig (2-tailed) is greater than 0.05 (.135) so there is no significant difference in critical thinking between education and nutrition majors. The null hypothesis is accepted.
  • One way ANOVA The null hypothesis is true, therefore the f value is closer to 1.0. The p value is greater than 0.05, which shows there is no sig. difference in critical thinking between the academic year groups.
  • T-test The sig (2-tailed) is greater than .05 (.732) so there is no significant difference between critical thinking between ethnicities. The null hypothesis is accepted.
  • Pearson r There is no relationship b etween critical thinking and cumulative GPA . The null hypothesis is accepted.
  • One Way ANOVA There is an inverse relationship between the f value and the p value. In this case, the f value is large and the p value is small. Because the p value is < 0.05, there is a sig. difference in critical thinking between the two age groups.
  • Pearson r There is no relationship b etween critical thinking and cumulative GPA in students aged 23 and under . The null hypothesis is accepted.
  • Pearson r There is no relationship b etween critical thinking and cumulative GPA in students aged 24 and over . The null hypothesis is accepted.
  • This table demonstrates the analysis results for critical thinking. As you can see, all null hypotheses were accepted except for the age groups, which demonstrates that there was a sig. difference in critical thinking across the two age groups at .030. Because of the sig. difference, the files were split to test the two age groups separately in order to determine which group was responsible for the significance. But as you can see, once split, there was no sig. difference.
  • These are the null hypotheses 18 thru 23 for MAI/SRL
  • T-test The sig (2-tailed) is greater than .05 (.795) so there is no significant difference in SRL between nutrition and education majors. The null hypothesis is accepted.
  • One Way ANOVA When the null hypothesis is true, the f value is closer to 1.0. The p value is greater than 0.05, which demonstrates there is no sig. difference in SRL between the academic year groups.
  • T-test The sig (2-tailed) is less than .05 (.020) so there is a significant difference in SRL between students 23 and under and students 24 and over. The null hypothesis is rejected.
  • Correlation is significant at the 0.01 level (2-tailed).
  • Correlation is significant at the 0.01 level (2-tailed).
  • A Pearson r was done for this analysis. There is a defined relationship between SRL, critical thinking and self-efficacy. So the higher the self-efficacy, the higher the self-regulatory behaviors (MAI score), and vice versa. The higher the critical thinking, the higher the self-regulatory behaviors (MAI score), and vice versa. The higher the self-efficacy, the higher the critical thinking scores reported, and vice versa. Because all three demonstrate significant differences, the null hypothesis is rejected.
  • For the d ifferences in MAI/SRL between majors, academic year and ethnicity groups, there were no sig. differences, so these 3 null hypotheses were accepted. But for differences between MAI/SRL and age groups there was a sig. difference, at .020, so the null hypothesis was rejected. For the r elationships between MAI/SRL and cumulative GPA across the age groups, there was no sig. difference in students 23 yrs and under, so this null H0 was accepted. There was, however, a sig. difference for those students 24 yrs and over, at .009, so this null H0 was rejected. The final hypothesis questioned whether there was a r elationship between MAI/SRL, critical thinking & self-efficacy. (go back to prev. slide)
  • Should I include his findings? Report findings about course GPA for SE & CT Report findings about cumulative GPA for SE, CT & SRL
  • Critical Thinking, Self-Efficacy, and Self-Regulated Learning in University Students

    1. 1. Critical Thinking, Self-Efficacy, and Self-Regulated Learning in University Students Cheryl Reining & Sarah Thelen Thesis Supervisor: Catherine Arnold, MS, EdD, RD, LDN
    2. 2. Background <ul><li>Increased interest in how student’s underlying beliefs about knowledge and knowing are a part of the learning process (1) </li></ul><ul><li>Critical thinking is a construct of self-regulated learning and is the primary reason for higher education (2) </li></ul><ul><li>Self-efficacy is a central influence on and relates positively to academic performance (3) </li></ul><ul><li>Self-regulated learners (SRL) have a high awareness of self, which enhances their ability to achieve their academic goals </li></ul>1. Hofer, 2001 2. Halpern, 1999 3. Bandura, 1989, Multon, Brown, Lent, 1991
    3. 3. Literature Review
    4. 4. Outcome Expectancies <ul><li>There are two components of expectancies </li></ul><ul><ul><li>1.) Expectancies for success: </li></ul></ul><ul><ul><ul><li>“ Refers to performance expectations, and relates specifically to performing a task” (4) </li></ul></ul></ul><ul><ul><li>2.) Self-efficacy: </li></ul></ul><ul><ul><ul><li>Self-efficacy is a self-assessment of one’s ability to master a task </li></ul></ul></ul>4. Pintrich, 2004
    5. 5. Critical Thinking <ul><li>“The degree to which students report applying previous knowledge to new situations in order to solve problems, reach decisions, or make critical evaluations with respect to standards of excellence” (5) </li></ul><ul><li>The researchers found critical thinking to be significantly associated with course grades </li></ul>5. Lynch, 2006
    6. 6. Self-regulated Learning <ul><li>SRL is the processes, or constructs, by which individual learners attempt to monitor and control their own learning </li></ul><ul><li>SRL is believed to include multiple constructs including background knowledge, metacognitive knowledge, metacognitive regulation, strategy use, epistemological beliefs and various motivational constructs (6) </li></ul><ul><li>Researchers found correlations between SRL, expectancy and critical thinking </li></ul>6. Sperling et al, 2004
    7. 7. Purpose <ul><li>To examine potential relationships between critical thinking strategies, expectancy (self-efficacy) and course grade in nutrition courses among undergraduate university students </li></ul><ul><li>To examine potential relationships between self-regulated learning, critical thinking, self-efficacy and cumulative GPA among undergraduate university students in education and nutrition courses </li></ul>
    8. 8. Methods
    9. 9. Methodology: Data Collection <ul><li>An e-mail was sent to Nutrition Department faculty requesting assistance in the administration of the in-class tool </li></ul><ul><li>The e-mail stated this was for a graduate research project, and the IRB proposal had been approved, it stated the general premise of the survey. It also stated it was a voluntary survey, that there was no right or wrong response, and that it would take approximately five minutes. </li></ul><ul><li>Surveys were completed in class, time estimated was 5 minutes per student </li></ul><ul><li>Surveys were returned in sealed envelopes </li></ul>
    10. 10. Measurement Tool: MSLQ <ul><li>Instrumentation: </li></ul><ul><ul><li>Motivated Strategies for Learning (MSLQ) questionnaire </li></ul></ul><ul><ul><ul><li>Self-report tool designed to assess motivation and learning strategies for a college course </li></ul></ul></ul><ul><ul><ul><ul><li>13 statements used to gauge critical thinking and self-efficacy </li></ul></ul></ul></ul>
    11. 11. Online Participant Recruitment <ul><li>Survey Administration </li></ul><ul><ul><li>E-mail invitations to Benedictine University students enrolled in Spring 2011 semester/quarter </li></ul></ul><ul><ul><li>3 separate e-mails – between April 28 th and May 10 th , 2011 </li></ul></ul><ul><ul><li>$100.00 incentive – random drawing </li></ul></ul><ul><ul><li>Written invitation – included in the In-Class survey packets </li></ul></ul>
    12. 12. Measurement Tool: Metacognitive Awareness Inventory (MAI) <ul><li>Instrumentation: </li></ul><ul><ul><li>Metacognitive Awareness Inventory (MAI) questionnaire </li></ul></ul><ul><ul><ul><li>Self-report tool designed to measure adult metacognitive awareness </li></ul></ul></ul><ul><ul><ul><ul><li>52 statements used to gauge knowledge of cognition and regulation of cognition </li></ul></ul></ul></ul>
    13. 13. Online Surveys <ul><li>Participants completed the online surveys via SurveyMonkey, a web-based survey service </li></ul><ul><li>Completed surveys were linked to Benedictine’s website (all information was kept confidential) </li></ul><ul><li>Survey responses – entered into Excel doc and exported into IBM SPSS 19 </li></ul>http://www.surveymonkey.com/
    14. 14. Data Analysis <ul><li>IBM SPSS 19 </li></ul><ul><ul><li>Frequency and Descriptive </li></ul></ul><ul><ul><li>Factor Analysis </li></ul></ul><ul><ul><li>Cronbach Alpha </li></ul></ul><ul><ul><li>One Way ANOVA </li></ul></ul><ul><ul><li>Independent t-test </li></ul></ul><ul><ul><li>Pearson r </li></ul></ul><ul><li>Independent </li></ul><ul><ul><ul><li>Age </li></ul></ul></ul><ul><ul><ul><li>Gender </li></ul></ul></ul><ul><ul><ul><li>Academic year </li></ul></ul></ul><ul><ul><ul><li>Ethnicity </li></ul></ul></ul><ul><ul><ul><li>Major </li></ul></ul></ul><ul><ul><li>Dependent/Independent </li></ul></ul><ul><ul><ul><li>MSLQ </li></ul></ul></ul><ul><ul><ul><ul><li>Critical thinking </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Self-efficacy </li></ul></ul></ul></ul><ul><ul><ul><li>MAI </li></ul></ul></ul><ul><ul><ul><li>Course grade </li></ul></ul></ul><ul><ul><ul><li>Cumulative GPA </li></ul></ul></ul>Variables
    15. 15. Findings: In-Class Survey
    16. 16. Participant Profile: Age Distribution In-Class Survey
    17. 17. Participant Profile: Ethnicity Distribution 66.3%
    18. 18. Participant Profile: Nutrition Major vs. Non-Nutrition Majors 86%
    19. 19. Analysis: Principle Component Analysis (PCA) <ul><li>The PCA was done to examine factors versus variables. </li></ul><ul><li>There were two factors that were created out of the variables- based on Eigenvalues less than 1. </li></ul><ul><li>The PCA results were an EXACT match to the results by the researchers who created the scale </li></ul><ul><li>The two factors were named: </li></ul><ul><ul><li>Self Efficacy (48.47% variance) </li></ul></ul><ul><ul><li>Critical Thinking (21.18% variance) </li></ul></ul>
    20. 20. Analysis: Cronbach Alpha Results Item N Cronbach’s Alpha Interpretation Self-Efficacy 8 .932 “ Excellent” Critical Thinking 5 .889 “ Good”
    21. 21. H01: There is no Difference in Self Efficacy & Critical Thinking between Majors <ul><li>Self efficacy: </li></ul><ul><ul><li>T = -2.487, df = 170, p = .014 </li></ul></ul><ul><ul><li>Nutrition: mean = 5.9122; Standard deviation = .84973 </li></ul></ul><ul><ul><li>Other: mean = 6.3646; Standard deviation = .66135 </li></ul></ul><ul><ul><li>Non-nutrition majors report greater levels of self-efficacy </li></ul></ul><ul><li>Critical thinking: </li></ul><ul><ul><li>T = -.187, df = 32.515, p = .853 </li></ul></ul><ul><ul><li>There is no significance between majors for either factor </li></ul></ul>
    22. 22. H02: There is no Difference in Self Efficacy & Critical Thinking between Age <ul><li>.656 (142) .513  No significance </li></ul><ul><li>Null Hypothesis accepted </li></ul>Levene's Test for Equality of Variances   F Sig. t df Sig. (2-tailed) self_efficacy Equal variances assumed 4.862 .029 .656 142 .513 Equal variances not assumed .575 61.074 .567
    23. 23. H03: There is no Difference in Self Efficacy between Academic Year Nutrition Majors Other <ul><li>.697 (24) .846  No Significance </li></ul><ul><li>1.922 (11) .138  No significance </li></ul><ul><li>Null Hypothesis Accepted </li></ul>
    24. 24. H04a: Self Efficacy does not Differ Across Course Grade in Nutrition Majors <ul><li>F=3.722 (24) p<.001  significance </li></ul><ul><li>Null hypothesis accepted </li></ul>ANOVA a grade Sum of Squares df Mean Square F Sig. Between Groups 41.393 24 1.725 3.722 .000 Within Groups 53.292 115 .463 Total 94.686 139 a. major_NUTR_other = Nutrition
    25. 25. H04b: Self efficacy does not Differ Across Course Grade in Non-Nutrition Majors <ul><li>1.138 (11) .412  no significance </li></ul><ul><li>Null hypothesis accepted </li></ul>ANOVA a grade Sum of Squares df Mean Square F Sig. Between Groups 4.000 11 .364 1.138 .412 Within Groups 3.833 12 .319 Total 7.833 23 a. major_NUTR_other = Other
    26. 26. H04: Self efficacy does not Differ Across Course Grade <ul><li>Nutrition Majors: </li></ul><ul><ul><li>t=5.663 (138) p<.001 (significant) </li></ul></ul><ul><ul><li>Grade A & B: N = 119, Mean = 6.0798, Std Dev = .76568 </li></ul></ul><ul><ul><li>Grade C, D, F: N = 21, Mean = 5.0655, Std Dev = .70225 </li></ul></ul><ul><li>Non-Nutrition Majors: </li></ul><ul><ul><li>t=.363 (22) p=.720 </li></ul></ul><ul><ul><li>Grade A & B: N = 23, Mean = 6.3750, Std Dev = .67420 </li></ul></ul><ul><ul><li>Grade C, D, F: N = 1, Mean = 6.1250 </li></ul></ul><ul><li>Null hypothesis accepted </li></ul>
    27. 27. H05a: There is no Relationship Between Self-Efficacy and Course Grade among Nutrition Majors <ul><li>The relationship between self efficacy and nutrition majors was investigated </li></ul><ul><li>N = 140, p = .496 </li></ul><ul><li>Null hypothesis rejected </li></ul>Correlations a grade self_efficacy grade Pearson Correlation 1 .496 ** Sig. (2-tailed) .000 N 140 140 self_efficacy Pearson Correlation .496 ** 1 Sig. (2-tailed) .000 N 140 148 **. Correlation is significant at the 0.01 level (2-tailed). a. major_NUTR_other = Nutrition
    28. 28. H05b: There is no Relationship Between Self-Efficacy and Course Grade Among Other Majors <ul><li>The relationship between self efficacy and other (non-nutrition majors) was investigated </li></ul><ul><li>N = 24, p = .255 </li></ul><ul><li>Null hypothesis accepted </li></ul>Correlations a grade self_efficacy grade Pearson Correlation 1 .242 Sig. (2-tailed) .255 N 24 24 self_efficacy Pearson Correlation .242 1 Sig. (2-tailed) .255 N 24 24 a. major_NUTR_other = Other
    29. 29. H06: Critical Thinking does not Differ Across Course Grade 2.586 (163) .011; F= .942 <ul><li>H06: Hypothesis Rejected </li></ul>Levene's Test for Equality of Variances F Sig. t df Sig. (2-tailed)     Critical thinking Equal variances assumed .942 .333 2.586 163 .011   Equal variances not assumed 2.400 26.546 .024  
    30. 30. H07: There is no Relationship Between Critical Thinking and Course Grade <ul><li>The relationship between critical thinking and course grade was investigated. N = 173, p = .127 </li></ul><ul><li>Null hypothesis accepted </li></ul>Correlations grade critical_think grade Pearson Correlation 1 .119 Sig. (2-tailed) .127 N 165 165 Critical thinking Pearson Correlation .119 1 Sig. (2-tailed) .127 N 165 173
    31. 31. In-Class Significant Findings <ul><li>Non-nutrition reported greater levels of self-efficacy than Nutrition majors </li></ul><ul><li>H05a: Significant finding between self efficacy and course grade (individual grades and categories) in nutrition majors </li></ul><ul><li>H06: Significant findings between critical thinking and course grade </li></ul>
    32. 32. Findings: Online Survey
    33. 33. Participants Profile: Gender & Age Distribution Total participants= 88 79 females = 90% 9 males = 10% Females age: 63 = 23 and under 16 = 24 and over Males age: 9 = 23 and under 0 = 24 and over
    34. 34. Participant Profile: Ethnicity Distribution Online Survey Total Participants = 88 67% White 33% Non-white 33% 67%
    35. 35. Participant Profile: Distribution by Major 40% 60% Total participants= 88 60% Education majors 40% Nutrition majors
    36. 36. MSLQ PCA <ul><li>MSLQ – consists of two factors: </li></ul><ul><ul><li>Critical thinking </li></ul></ul><ul><ul><li>Expectancy (self-efficacy) </li></ul></ul><ul><li>There was an exact match to the scale for undergraduate Nutrition majors and undergraduate Education majors, but there was a significant mismatch between all other majors. </li></ul><ul><ul><li>Thus, for purposes of this study, which included the intent to focus on nutrition majors, only the results from Nutrition and Education were retained </li></ul></ul>
    37. 37. MAI PCA <ul><li>MAI – consists of two broad categories containing multiple factors: </li></ul><ul><ul><li>Knowledge of cognition </li></ul></ul><ul><ul><li>Regulation of cognition </li></ul></ul><ul><li>There was a significant mismatch between ‘all majors’ and MAI PCA results reported by the researchers (Gregory Shraw & Rayne Sperling Dennison), who developed the scale, therefore the factors could not be used in the data analyses </li></ul><ul><li>There was a mismatch between Nutrition and Education and all other majors, which suggests different SRL skills are utilized by different majors </li></ul>
    38. 38. MAI Scale Scale: MAI A high value for Cronbach’s Alpha (> .9), indicates an excellent internal consistency Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .976 .977 52 Item Statistics Mean Std. Deviation Score Interpretation Stop and reread 89.55 18.630 Good Use strategies from past 88.75 18.304 Good Good judge of understanding 87.78 15.863 Good Consider all options 68.58 29.483 Questionable Learned as much as could have 67.89 29.188 Questionable Question material prior 60.24 32.666 Questionable
    39. 39. Cronbach Alpha: Reliability A high value for Cronbach’s Alpha (> .9), indicates an excellent internal consistency of the items in the scale. Factor N Alpha Score Score Interpretation Critical thinking 5 .902 Excellent Self-efficacy 8 .944 Excellent MSLQ 13 .933 Excellent MAI 52 .977 Excellent
    40. 40. Null Hypotheses for Self-efficacy Null H08 - Null H012b
    41. 41. H08: There is No Difference Between Majors in Self-efficacy Null H0 is rejected Majors http://www.clker.com/clipart-thumb-up.html t = 2.125 df = 86 Self-efficacy N Mean Education 53 6.2382 Nutrition 35 5.8607 sig. .036
    42. 42. H09a : There is No Difference in Self-efficacy Between Academic Years for Nutrition Majors Null H0 is accepted Nutrition f = 1.833 df = 3, 31 Self-efficacy N Mean Freshman 7 5.6964 Sophomore 3 5.4583 Junior 11 5.5341 Senior 14 6.2857 Total 35 5.8607 sig. .162
    43. 43. H09b : There is No Difference in Self-efficacy Between Academic Years for Education Majors Education f = 3.919 df = 3, 49 Null H0 is rejected Self-efficacy N Mean Freshman 6 5.8958 Sophomore 8 5.5938 Junior 17 6.4779 Senior 22 6.3807 Total 53 6.2382 sig. .014
    44. 44. H010a: There is No Difference in Self-efficacy Between Age Categories for Nutrition Majors Nutrition f = 2.770 df = 1, 33 Null H0 is accepted Self-efficacy N Mean 23 and under 26 5.7115 24 and over 9 6.2917 Total 35 75.860 sig. .106
    45. 45. H010b: There is No Difference in Self-efficacy Between Age Categories in Education Majors Education f = 2.068 df = 1, 51 Null H0 is accepted Self-efficacy N Mean 23 and under 46 6.1821 24 and over 7 6.6071 Total 53 6.2382 sig. .156
    46. 46. H011a: There is No Difference in Self-efficacy Between Ethnicity Groups in Nutrition Majors Nutrition Null H0 is accepted t = 1.555 df = 33 Self-efficacy N Mean White 23 6.0326 Non-white 12 5.5313 sig. .130
    47. 47. H011b: There is No Difference in Self-efficacy Between Ethnicity Groups in Education Majors Null H0 is accepted Education t = 1.665 df = 50 Self-efficacy N Mean White 36 6.3403 Non-white 16 5.9766 sig. (2-tailed) .102
    48. 48. H012a: There is No Relationship Between Self-efficacy and Cumulative GPA in Nutrition Majors Null H0 is accepted Correlations Nutrition gpa self-efficacy gpa Pearson Correlation 1 .308 Sig. (2-tailed) .076 N 34 34 self-efficacy Pearson Correlation .308 1 Sig. (2-tailed) .076 N 34 35 Correlation is significant at the 0.01 level (2-tailed).
    49. 49. H012b: There is No Relationship Between Self-efficacy and Cumulative GPA in Education Majors Null H0 is rejected Correlations Education gpa self-efficacy gpa Pearson Correlation 1 .449 ** Sig. (2-tailed) .001 N 53 53 self-efficacy Pearson Correlation .449 ** 1 Sig. (2-tailed) .001 N 53 53 Correlation is significant at the 0.01 level (2-tailed).
    50. 50. Results of Self-efficacy Analyses Hypotheses for Self-efficacy Null H0 for Self-efficacy & … Sig. H08 Majors .036 H09a Academic year for NUTR. majors .162 H09b Academic year for Ed. majors .014 H010a Age categories for NUTR. Majors .106 H010b Age categories for Ed. majors .156 H011a Ethnicities for NUTR majors .130 H011b Ethnicities for Ed. majors .102 H012a Cumulative GPA for NUTR. majors .076 H012b Cumulative GPA for Ed. majors .001
    51. 51. Null Hypotheses for Critical Thinking Null H013 - Null H017b
    52. 52. H013: There is No Difference in Critical Thinking Between Majors Null H0 is accepted Majors t = 1.509 df = 86 Critical thinking N Mean Education 53 5.5283 Nutrition 35 5.1657 sig. .135
    53. 53. H014: There is No Difference in Critical Thinking Across Academic Years f = 1.973 df = 3, 84 Null H0 is accepted Academic Year Critical Thinking N Mean Freshman 13 5.1077 Sophomore 11 4.7636 Junior 28 5.4929 Senior 36 5.5889 Total 88 5.3841 sig. .124
    54. 54. H015: There is No Difference in Critical Thinking Across Ethnicity Groups Null H0 is accepted t = .343 df = 85 Critical Thinking N Mean White 59 5.4169 Other 28 5.32876 sig. .732
    55. 55. H016: There is No Relationship Between Critical Thinking and Cumulative GPA Correlation is significant at the 0.01 level (2-tailed). Null H0 is accepted Correlations gpa critical_thinking gpa Pearson Correlation 1 .071 Sig. (2-tailed) .516 N 87 87 Critical thinking Pearson Correlation .071 1 Sig. (2-tailed) .516 N 87 88
    56. 56. H017: There is No Difference in Critical Thinking Across Age Groups Age Null H0 is rejected f = 4.840 df = 1, 86 Critical Thinking N Mean 23 and under 72 5.2639 24 and over 16 5.9250 Total 88 5.3841 sig. .030
    57. 57. H017a: There is No Relationship Between Critical Thinking and Cumulative GPA in Students Aged 23 and Under Null H0 is accepted Correlations 23 and under gpa critical_thinking gpa Pearson Correlation 1 .140 Sig. (2-tailed) .241 N 72 72 Critical thinking Pearson Correlation .140 1 Sig. (2-tailed) .241 N 72 72 Correlation is significant at the 0.01 level (2-tailed).
    58. 58. H017b: There is No Relationship Between Critical Thinking and Cumulative GPA in Students Aged 24 and Over Null H0 is accepted Correlations 24 and over gpa critical_thinking gpa Pearson Correlation 1 -.278 Sig. (2-tailed) .316 N 15 15 Critical thinking Pearson Correlation -.278 1 Sig. (2-tailed) .316 N 15 16 Correlation is significant at the 0.01 level (2-tailed).
    59. 59. Results for Critical Thinking Analyses Hypotheses for Critical Thinking Null H0 for Critical Thinking & … Sig. H013 Majors .130 H014 Academic year .124 H015 Ethnicity groups .732 H016 Cumulative GPA .516 H017 Age groups .030 H017a Cumulative GPA in 23 years and under .241 H017b Cumulative GPA in 24 years and over .316
    60. 60. Null Hypotheses for MAI/SRL Null H018 - Null H023
    61. 61. H018: There is No Difference in MAI/SRL Between Majors Null H0 is accepted Majors t = .261 df = 86 MAI/SRL N Mean Education 53 80.0708 Nutrition 35 79.1797 sig. .795
    62. 62. H019: There is No Difference in MAI/SRL Between Academic Years f = 3.84 df = 3, 84 Null H0 is accepted MAI/SRL N Mean Freshman 13 76.0740 Sophomore 11 70.6818 Junior 28 83.1408 Senior 36 81.1287 Total 88 79.7163 sig. .107
    63. 63. H020: There is No Relationship Between MAI/SRL and Ethnicity Null H0 is accepted t = 1.026 df = 85 MAI/SRL N Mean White 59 80.6750 Other 28 77.0165 sig. (2-tailed) .308
    64. 64. H021: There is No Difference Between MAI/SRL and Age Groups Null H0 is rejected t = - 2.365 df = 86 MAI/SRL   N Mean 23 and under 72 77.9111 24 and over 16 87.8401 sig. .020
    65. 65. H022a: There is No Relationship Between MAI/SRL and Cumulative GPA in Students Aged 23 and Under Null H0 is accepted Correlations 23 and under gpa MAI gpa Pearson Correlation 1 -.070 Sig. (2-tailed) .558 N 72 72 MAI Pearson Correlation -.070 1 Sig. (2-tailed) .558 N 72 72 Correlation is significant at the 0.01 level (2-tailed).
    66. 66. H022b: There is No Relationship Between MAI/SRL and Cumulative GPA in Students Aged 24 and Over Null H0 is rejected Correlations 24 and over gpa MAI gpa Pearson Correlation 1 .651 ** Sig. (2-tailed) .009 N 15 15 MAI Pearson Correlation .651 ** 1 Sig. (2-tailed) .009 N 15 16 Correlation is significant at the 0.01 level (2-tailed)
    67. 67. H023: There is No Relationship Between MAI/SRL, Critical Thinking & Self-efficacy MAI/SRL, Critical Thinking & Self-efficacy Null H0 is rejected Correlations MAI Critical thinking self-efficacy MAI/SRL Pearson Correlation 1 .340 ** .312 ** Sig. (2-tailed) .001 .003 N 88 88 88 Critical thinking Pearson Correlation .340 ** 1 .524 ** Sig. (2-tailed) .001 .000 N 88 88 88 self-efficacy Pearson Correlation .312 ** .524 ** 1 Sig. (2-tailed) .003 .000 N 88 88 88 **Correlation is significant at the 0.01 level (2-tailed).
    68. 68. Results for MAI/SRL Analyses Hypotheses for MAI/SRL Null H0 for MAI/SRL & … Sig. H018 Majors .795 H019 Academic year .107 H020 Ethnicity groups .308 H021 Age groups .020 H022a Cumulative GPA in 23 yrs and under .558 H022b Cumulative GPA in 24 yrs and over .009 H023 Critical thinking & self-efficacy .003
    69. 69. Summary <ul><li>As with Sperling et al (2004), significant correlations between the MAI/SRL component and the MSLQ critical thinking and self-efficacy scales for undergraduate students were found </li></ul><ul><li>The greatest significant findings in SRL were found in students: </li></ul><ul><ul><li>24 and older </li></ul></ul><ul><ul><li>with greater self-efficacy </li></ul></ul><ul><ul><li>with a major in Education </li></ul></ul>
    70. 70. Strengths <ul><li>Use of existing questionnaires that are valid, reliable and easily accessible </li></ul><ul><ul><li>In-Class </li></ul></ul><ul><ul><ul><li>Captive audience </li></ul></ul></ul><ul><ul><ul><li>Overall participation response rate = 77% (209 out of a possible 272) </li></ul></ul></ul><ul><ul><li>Online </li></ul></ul><ul><ul><ul><li>Cash incentive </li></ul></ul></ul><ul><ul><ul><li>Intercorrelations between self-efficacy, critical thinking and SRL consistent with what the researchers found </li></ul></ul></ul><ul><ul><ul><li>High Cronbach Alpha scores demonstrate high validity and reliability to findings </li></ul></ul></ul><ul><ul><ul><li>High Cronbach Alpha scores excellent for SRL – demonstrates high reliability </li></ul></ul></ul>
    71. 71. Limitations and Future Research <ul><li>Limitations </li></ul><ul><ul><li>Data was collected during one semester/quarter only </li></ul></ul><ul><ul><li>Data was only collected from one university </li></ul></ul><ul><ul><li>Campus e-mails not always read </li></ul></ul><ul><ul><li>Online survey was time-consuming causing: </li></ul></ul><ul><ul><ul><li>A few participants to answer all of the questions with the same response </li></ul></ul></ul><ul><ul><ul><li>Incomplete data </li></ul></ul></ul><ul><li>Future Research – comparisons of: </li></ul><ul><ul><li>Other nutrition programs </li></ul></ul><ul><ul><li>Graduates vs. undergraduates </li></ul></ul>
    72. 72. References <ul><li>1. Hofer, B.K. Personal epistemology research: Implications for learning and teaching. Educational Psychology Review. 2001;13:353-383. </li></ul><ul><li>2. Halpern, D.E. Teaching for critical thinking: helping college students develop the skills and dispositions of a critical thinker. New Directions for Teaching and Learning. 1999;80:69-74. </li></ul><ul><li>3. Bandura, A. Human agency in social cognitive theory. American Psychologist . 1989;44:1179-1184. </li></ul><ul><li>Multon, K. D., Brown, S. D., Lent, R.W. Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling Psychology. 1991; 38:30-38. </li></ul><ul><li>4. Pintrich, P.R., A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students. Educational Psychology Review . 2004;16 (4) </li></ul><ul><li>5. Lynch, D.J., Motivation Factors, Learning strategies, and resources management as predictors in course grades. The College Student Journal . 2006;40(2): 423-428 </li></ul><ul><li>6. Sperling, R.A., Howard, B.C., Staley, R., DuBois, N. Metacognition and self-regulated learning constructs. Educational Research and Evaluation. 2004;10:117-139. </li></ul>
    73. 73. Thank You! Any Questions?

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