The relationship between persistence, academic

engagement and academic achievement among post graduate students of OUM

The relationship between persistence, academic

engagement and academic achievement among post graduate students of OUM

By:Assoc. Prof. Dr. Nagarajah Lee

Assoc. Prof. Dr. Chung Han TeckProf. Dr. Rahmah Hashim.

Assoc. Prof. Dr Lim Tick Meng

OverviewOverview

• Background• Purpose• Research Design, Population & Sample• Instrument• Findings• Conclusion & Recommendation

BackgroundBackground

• Educational institutions have traditionally used academic variables such as grade point average (GPA), college admissions tests, and coursework grades (Adelman, 1999; Kern, Fagley, & Miller, 1998; Robbins et al., 2003; Tinto, 1997) to identify at-risk students.

• However evidence from the literature indicates that non-academic factors often have an even greater impact on academic performance. Among the variables that are found to have significant association with students’ performance are institutional and degree commitment, academic and social integration, support services satisfaction, finances, social support, and personality and psychological adjustment (Milem & Berger, 1997; Pascarella, 1985; Stage & Rushin, 1993; Tinto, 1993).

Background - contBackground - cont

• Several studies have highlighted the significant role of affective factors on learning (e.g., Mathewson, 1994; Wigfield, 1997), particularly student engagement.

• Student engagement has been popularly used as an indicator of successful classroom instruction and predictor of students’ academic success (Bonia et.al 1997).

• Student engagement also refers to as "student's willingness, need, desire and compulsion to participate in, and be successful in, the learning process promoting higher level thinking for enduring understanding.” Willms, J.D (2003).

• Students’ engagement is viewed as motivated behavior which can be seen from the kinds of cognitive strategies students choose to use, and by their willingness to persist with difficult tasks by regulating their own learning behavior.

• Persistence on the other hand is defined as adults staying in programs for as long as they can, engaging in self-directed learning, temporarily leaving the program, and returning to a program as soon as the demands of their lives allow (Beder, 1991). Persistence in this sense refers to the tendency or willingness of an adult learners to stay on a programme they have enrolled in.

• Both engagement and persistence are psychological factors that can be used as indicators to gauge students’ seriousness in their studies. It is therefore postulated both the factors can be reliable predictors of academic performance.

Due to the paucity of research that Due to the paucity of research that examines both student engagement examines both student engagement and student persistence in studies and student persistence in studies simultaneously in relation to academic simultaneously in relation to academic performance, this study proposes to performance, this study proposes to incorporate both the factors in a incorporate both the factors in a statistical model to determine their statistical model to determine their validity as predictors of students’ validity as predictors of students’ academic performanceacademic performance

Purpose Purpose

Conceptual FrameworkConceptual Framework

Student Engagement in Academic Activities

Student Persistence in Studies

Academic Performance

Research Design, Research Design, Population & SamplePopulation & Sample

• This is a cross sectional survey using self- administered questionnaire.

• The population for this study comprises all postgraduate students of OUM enrolled in Masters degree programs and were actively taking service during the September 2010 semester.

• The sample consists of 390 randomly selected students from 4 masters programs (MBA, MEd, MHRM, MM and Nursing) from 13 learning centers.

INSTRUMENTINSTRUMENT

Student Persistent Scale

a) Academic Integration

b) Service Satisfaction

c) Degree Commitment

d) Academic Conscientiousness

e) Institutional Commitment

Student Engagement Scale

a) Classroom Behaviour

b) Cognitive Emphasis

c) Academic Contribution

Respondents are required to rate their perceptions on a five-point Likert scale

Student Engagement Student Engagement ScaleScale

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CMIN/df = 5.817

Model df GFI AGFI RMSEA NFI CFI PNFI PGFI3-factor oblique

506.095 87 0.88 0.87 0.061 0.88 0.89 0.77 0.84

3-factor orthogonal

529.48 89 0.81 0.78 0.080 0.70 0.79 0.61 0.69

One factor 769.45 89 0.68 0.63 0.11 0.54 0.61 0.49 0.58

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Goodness of Fit

Student Persistent ScaleStudent Persistent Scale

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CMIN/df = 6.269

Model df GFI AGFI RMSEA NFI CFI PNFI PGFI5-factor oblique

1260.88 220 0.91 0.90 0.053 0.93 0.91 0.89 0.93

5-factor orthogonal

1335.63 228 0.84 0.82 0.089 0.86 0.79 0.78 0.74

One factor 2135.54 228 0.61 0.60 0.11 0.56 0.52 0.42 0.51

2

ReliabilityReliability

Constructs Cronbach Alpha Coefficient

Student Engagement Scale

1. Classroom Behaviour 0.780

2. Cognitive Emphasis 0.895

3. Academic Contribution 0.879

Student Persistence Scale

1. Academic Integration 0.928

2. Service Satisfaction 0.835

3. Degree Commitment 0.786

4. Academic Conscientiousness

0.866

5. Institutional Commitment 0.840

Variable Frequency Percentage (%) Variable Frequency Percentage (%)

Gender EthnicityFemale 148 37.6 3.75 and above 46 11.8Male 242 62.4 3.67 to 3.74 33 8.5Total 390 100.0 3.00 to 3.67 194 49.7Program Below 3.00 56 14.4MBA 112 28.7 Missing 61 15.6Med 231 59.2 Total 390 100.0MHRM 5 1.3 Learning CenterMM 16 4.1 Ipoh Greenhill 43 11.0Nursing 26 6.7 Johor Bharu 34 8.7Total 390 100.0 Kedah 30 7.7SEMESTER Kelantan 41 10.51 59 15.1 Kuala Lumpur 42 10.82 98 25.1 Kuching 37 9.53 73 18.7 Melaka 37 9.54 35 9.0 Miri 18 4.65 47 12.1 NS 13 3.36 18 4.6 Pahang 17 4.47 13 3.3 Penang 33 8.58 7 1.8 Sabah 18 4.6Missing 40 10.3 Terengganu 27 6.9Total 390 100.0 Total 390 100.0EthnicityMalay 189 48.5Chinese 117 30.0Indian 66 16.9Others 18 4.6Total 390 100.0

Respondents’ Demography

Respondent Demography Respondent Demography vs CGPAvs CGPA

CGPA Categoryp - value

(Chi-Square)

Less than 3.003.00 and

above

Gender

Female 21 (16.9%) 103 (83.1%)0.943

Male 35 (17.2%) 168 (82.8%)

Ethnicity

Malay31 (20.1%) 123 (79.9%)

0.164Chinese 12 (12.2%) 87 (87.9%)

Indian 6 (10.3%) 52 (89.7%)

Others 7 (38.9%) 11 (61.1%)

Age

30 and below 14 (25.5%) 41 (74.5%)

0.07931 to 40 26 (20.0%) 104 (80.0%)

41 to 50 11 (12.9%) 74 (87.1%)

Above 50 5 (9.3%) 49 (90.7%)

Gender, Ethnicity, and Age are not significantly associated with students academic performance. A

single predictive model can be used to represent the post graduate student population

* P <.05

Student Engagement vs Student Engagement vs CGPACGPA

Variable and Construct

CGPA N Mean SDp-value

(Mann-Whitney )

Classroom BehaviorLess than 3.00 56 2.86 0.46

0.0093.00 and above 271 3.13 0.57

Cognitive EmphasisLess than 3.00 56 2.92 0.50

0.0113.00 and above 271 3.12 0.60

Perceived Academic contribution

Less than 3.00 56 3.15 0.570.176

3.00 and above 271 3.28 0.58

EngagementLess than 3.00 56 2.94 0.43

0.0613.00 and above 273 3.08 0.46

Classroom behaviour and cognitive emphasis are significantly related to students academic performance.

Students’ perceived academic contribution is not associated with their academic performance.

* P <.05

Student Persistence vs Student Persistence vs CGPACGPA

Variable and Construct

CGPA N MeanStd.

Deviationp-value

Academic Integration

Less than 3.00 56 3.91 0.610.012

3.00 and above 273 4.06 0.44

Institutional Commitment

Less than 3.00 56 3.81 0.730.673

3.00 and above 271 3.84 0.60

Service satisfactionLess than 3.00 56 4.09 0.83

0.0053.00 and above 273 4.43 0.59

Academic Conscientiousness

Less than 3.00 56 4.11 0.710.022

3.00 and above273 4.34 0.57

Degree Commitment

Less than 3.00 56 3.84 0.610.011

3.00 and above 273 4.09 0.61

PersistenceLess than 3.00 56 3.95 0.63

0.0693.00 and above 273 4.15 0.41

Academic Integration, Service Satisfaction, Degree Commitment, Academic Conscientiousness are significantly

associated with students’ academic performance.There is no significant association between Institutional

Commitment students’ academic performance.

* P < .05

The Logistic Regression The Logistic Regression ModelModel

  B S.E. Wald df Sig. Exp(B)Step 1a Behavior 0.784 0.348 5.075 1 0.010 2.190

Cognitive 0.693 0.355 3.811 1 0.041 2.000Academic 0.409 0.352 1.350 1 0.246 1.505Academic Integration 1.324 0.54 6.012 1 0.008 3.758Institutional Commitment 1.122 0.461 5.924 1 0.015 3.071Service satisfaction 0.353 0.323 1.194 1 0.144 1.423Academic Conscientiousness

0.648 0.326 3.951 1 0.032 1.912Degree Commitment

0.734 0.368 3.978 1 0.046 2.083Constant -20.78 6.673 18.601 1 0  

a. Variable(s) entered on step 1: Behavior, Cognitive, Academic, Academic Integration, Institutional Commitment, Service Satisfaction, Academic Conscientiousness, Degree Commitment.

Model FitModel Fit

Hosmer and Lemeshow Test

Step Chi-square df Sig.1

13.474 8 .197

Model Summary

Step -2 Log likelihoodCox & Snell R

SquareNagelkerke R

Square1 270.795a .181 .234

a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Model Sensitivity & Model Sensitivity & SpecificitySpecificity

Area Under the Curve

Test Result Variable(s):Predicted probability

AreaStd.

Errora

Asymptotic Sig.b

Asymptotic 95% Confidence Interval

Lower Bound

Upper Bound

.704 .039 .000 .627 .781

a. Under the nonparametric assumption

b. Null hypothesis: true area = 0.5

Classification Tablea

   

Observed

Predicted

CGPA CategoryPercentage Correct

Less than 3.00

3.00 and above

Step 1 CGPA Category

Less than 3.00 45 9 83.333.00 and above 24 244 91.04

Overall Percentage      a. The cut value is .500      

Sensitivity [ability to predict event correctly] = 83.33 %

Specificity [ability to predict non event correctly] = 91.04%

Logistic Model Explaining the relationshipsLogistic Model Explaining the relationships

CGPA 3.00 and above = -20.78 + 0.784 (Behavior) +0.693 (Cognitive) +

1.324( Academic Integration) + 1.122 (Institutional Commitment) + 0.648 (Academic Conscientiousness) +

0.738 (Degree Commitment)

Based on this equation, the probability for a student to get a CGPA of 3.00 and above is:

P (E) = Z

Z

e

e

1

Sample computation of Sample computation of probabilityprobability

VariableCoefficient Students Rating

Constant -20.78 1

-20.7

8

Behaviour 0.784 43.13

6

Cogintive 0.693 42.77

2Academic Integration 1.324 4

5.296

Ins. Commitment 1.112 44.44

8Academic Conscientiousness 0.648 4

2.592

Degree Commitment 0.738 5 3.69

Probability of getting CGPA 3.00 and above is

0.760

Conclusion & RecommendationsConclusion & Recommendations• The findings of this study suggest that student engagement and persistence can be used as predictors of students academic performance.• Using student engagement and persistence, a process measure, as predictors of academic achievement would enable the academic institutions to identify ‘at risk’ students much earlier compared to using CGPA, which is a product measure.• Student engagement and persistence should ideally be used in conjunction with CGPA to identify ‘at risk’ students. This would enable academic institutions to formulate more effective intervention strategies to reduce attrition rate.

Thank YouThank You

Questions and comments are welcome