STANDARDISATION OF THE ACADEMIC READINESS QUESTIONNAIRE

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MOTIVATION FOR THE RESEARCH

The motivation for this study emanates against the backdrop of the national educational circumstances; these include the limited ‘pool’ of students with endorsement, the readiness of the students who have endorsement, the need for social transformation in terms of equity of access, the low graduation rates and the high attrition rates of students who are in the system, and the high demand for financial service professionals in the market place (CHE, 2009). The demands placed on the Faculty of Economic and Management Sciences at the University of Pretoria are similar to South African contact universities with the same drivers taking precedence; namely to improve the graduation rate and decrease the attrition rate of first-time entering first-year students, the need to address equity of access and to supply the high demand for well equipped financial service professionals. The Faculty of Economic and Management Sciences at the University of Pretoria is the largest faculty amongst eight other faculties and contributes 24.6% of all undergraduate enrolments for the 2008 cohort (BIRAP, 2008). The University of Pretoria is a large, research intensive ‘contact’ institution that provides tuition to both under- and postgraduate students. The majority of programmes are full-time and contact-based, where students have to attend classes and practical and tutorial sessions. In 2008, student numbers totalled 57 409 (38 934 contact and 18 475 distance) (University of Pretoria webpage). Pre-1994 the university was characterised as a ‘Historically White (Afrikaans) University’ (Bunting, 2006a, p. 50), but is currently a dual medium university that provides tuition in both English and Afrikaans (University of Pretoria webpage).

SCOPE OF THE STUDY

Readiness for university education fits within the broad and encompassing field of student retention and success. The most basic model to explain this framework is from Astin’s (1970) model of student development which indicates three distinct components of a higher education institution, namely Input – Environment – Output. The inputs refer to the abilities, skills and expectations that students bring with them to the university. The inputs that Astin refers to are associated with the elements of readiness for university education as explained by Conley (2007). The environment refers to all the elements of the institution that influences the learning experiences of students. According to Wend (2006), the student learning experience can be defined as the variety of experiences within the sphere of the University’s responsibility that students come in contact with and which influences learning. The student learning experience is therefore all-embracing and includes matters such as curricula, methods of teaching, learning and assessment, learning environment and resources, student progress and achievement, and academic and pastoral support.

Family background

Tinto refers to the work of authors like Weidman (1985) and Bean and Vesper (1990) to show how the ‘external communities’ influence persistence (Tinto, 1993, p. 62). The relationship between the intentions or goals and the external communities has the following pattern of interaction: students who have weak intentions to stay at university and poor goals could be influenced positively by external communities where these communities motivate the student to persist. The external communities could influence the persistence behaviour negatively in terms of a lack of support (Stage & Hossler, 2000, p. 179). Based on these premises, Tinto made a hypothesis that students from communities with high academic non-involvement (first-generation students) are more at risk for withdrawal (see Furr & Elling, 2002). The 90 reason is that the home or community social groups do not necessarily understand the transition that the student has to make and that the student is ‘…forced to at least partially reject membership in communities that have been part of their upbringing’ (Tinto, 1993, p. 62). Just as parental influence for first-generation students have a negative effect on persistence, it can have a positive effect too. Authors like Jones et al. (2008) and Johnston (2000) show that first-generation students are actually more likely to persist because of high levels of motivation. Parents, for example, can provide additional motivational support to students. Motivational support from parents could however, if too forceful, actually lead to students withdrawing rather than persisting. According to Tinto (1993, p. 63), this tension between parental support being too demanding or being totally uninvolved is particularly intensely experienced by first-generation students.

Financial pressures

According to Schuh (2005, p. 279), students and institutions find it challenging to secure funds for students to access higher education and for institutions to provide higher education. Students, according to Schuh, usually pay for higher education through savings, their parents, bursaries or loans. The impact of finances was regarded as very straight forward by many researchers, but Tinto argues that there are unresolved questions on the ‘how’ and ‘why’ finances has an effect on persistence (Tinto, 1993, p. 65). According to Tinto, the greatest effect of family finances is seen at or before entry to university. Students with financial difficulty will have to decide on the type of institution and which degree to enrol for if additional support in the form of loans or bursaries is not 91 available, or not to study at all. According to Astin (1975, p. 53), parental financial support increases the probability of a student persisting at a higher education institution (see Bean, 2005, p. 235). Astin (1975, p. 35) shows a direct relation between the financial income of parents and withdrawal rates. According to the results of Astin, the effect of parental income becomes insignificant in a regression analysis with other variables. This indicates that other variables influence the effect of parental income and withdrawal. ‘The greater dropout-proneness of students from low-income families is attributable to their less educated parents, lesser ability and lower motivation, and greater concern about finances’ (Astin, 1975, p. 35). According to Astin and Oseguera (2005), the educational level of both parents contributes to students completing their degrees. Parental education level is most often associated with the socio-economic status (SES) of the family (Astin, 1975; Furr & Elling, 2002).

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Work responsibilities

The financial situation of the family affects students’ decisions to work part-time to supplement the educational expenses and living costs while studying. Result from Schuh’s (2005, p. 282) study indicates that it is the students from low-income and middle-income families that are more likely to work during the year – an average of 22.6 hours per week (see Macgregor, 2007; Tinto, 2008). Bean states that working more than 20 hours per week could have negative consequences for the academic and social life of the student (2005, p. 236). Working full-time, according to Schuh (2005, p. 282), is negatively associated with persistence. Thus working full-time lowers persistence levels. The effect of work responsibilities is not always straight forward in terms of outcomes. Tinto states that work obligations, especially work off-campus that is not related to the academic programme will limit the time available for interaction with academic staff and peers (Tinto, 1993, p. 63). The reason for this is caused by the added responsibilities of commuter students, like family and work responsibilities. Astin (1975, p. 79) however indicates that part-time work facilitates persistence in some cases, because some students are able to spend time on work without suffering the negative consequences from a lack of lecturer and peer involvement. Students who work to earn money to pay for their studies are usually more motivated to complete their studies than the students who work to support their social expenditure (Bean, 2005, p. 236).

Institutional residence

Institutional residences are seen as an extension of the university environment and according to Astin (1975), living in university residences influences persistence. According to Astin and Oseguera (2005, p. 260), students who live in residence are more likely to complete their degrees (see Astin, 1975, p. 92). The research in Astin (1975) shows that living in university residences is associated with lower probabilities of withdrawal compared with living with parents or in private residences, irrespective of race or gender. Astin’s theory on this research outcome is that students living at university residences are more involved with campus activities than commuting students. Research in Tinto (1993) confirms the advantages of being socially and academically integrated into the communities of the university.

TABLE OF CONTENTS :

  • SUMMARY
  • CHAPTER 1 INTRODUCTION
    • 1.1. BACKGROUND
    • 1.2. MOTIVATION FOR THE RESEARCH
    • 1.3. SCOPE OF THE STUDY
    • 1.4. AIM OF THE STUDY
    • 1.5. RESEARCH DESIGN
    • 1.6. LEVEL OF ANALYSIS
    • 1.7. STUDENT LIFE CYCLE
    • 1.8. LAYOUT OF THE STUDY
  • CHAPTER 2 LITERATURE REVIEW
    • 2.1. INTRODUCTION
    • 2.2. KEY CONCEPTS CLARIFIED
      • 2.2.1 Retention
      • 2.2.2 Withdrawal
      • 2.2.3 Non-cognitive Variables
    • 2.2.4 Persistence
    • 2.3. LITERATURE DISCUSSION
    • 2.3.1. Readiness Theory
    • 2.3.2. Transition Theory
    • 2.3.3. Tinto’s Longitudinal Model of Institutional Departure
    • 2.3.4. Theory of Student Departure for Residential and Commuter Colleges
    • 2.3.5. Psychological Model of Student Retention
    • 2.3.6. Evaluation of Bean and Eaton’s Model
    • 2.4. ENTRY CHARACTERISTICS, WITHDRAWAL AND ACADEMIC ACHIEVEMENT
    • 2.4.1. Non-Cognitive Predictors
    • 2.4.2. Personal and Demographic Characteristics
    • 2.4.3. Cognitive Predictors
    • 2.5. THE RELATIONSHIP BETWEEN WITHDRAWAL AND ACADEMIC ACHIEVEMENT
    • 2.6. DEVELOPMENT OF A READINESS AND RETENTION MODEL
    • 2.7. CONCLUSION
  • CHAPTER 3 QUESTIONNAIRE DEVELOPMENT
    • 3.1. INTRODUCTION
    • 3.2. QUESTIONNAIRE REVIEW
      • 3.2.1. Non-Cognitive Questionnaire (NCQ)
      • 3.2.2. Survey of Academic Orientations (SAO)
      • 3.2.3. Trait Self-Regulation Inventory (TSRI)
      • 3.2.4. Motivated Strategies for Learning Questionnaire (MSLQ)
      • 3.2.5. Institutional Integration Scale (IIS)
      • 3.2.6. Vocational Identity Scale (VIS)
      • 3.2.7. Metacognitive Awareness Inventory (MAI)
      • 3.2.8. Locus of Control Inventory (LCI)
      • 3.2.9. International Personality Item Pool (IPIP)
      • 3.2.10. Alpha Baseline Questionnaire (ABQ)
    • 3.3. ACADEMIC READINESS QUESTIONNAIRE DEVELOPMENT
      • 3.3.1. Planning Phase
      • 3.3.2. Item Selection
      • 3.3.3. Construct and Pilot Testing of the Questionnaire
      • 3.3.4. Item Analysis
      • 3.3.5. Revising and Standardising the Questionnaire
      • 3.3.6. Technical Evaluation and Establishing Norms
    • 3.4. THE ACADEMIC READINESS QUESTIONNAIRE
    • 3.5. CONCLUSION
  • CHAPTER 4 METHODOLOGY
    • 4.1. INTRODUCTION
    • 4.2. AIM OF THE STUDY
    • 4.3. SAMPLING DESIGN AND METHODOLOGY
    • 4.4. DATA COLLECTION
    • 4.4.1. Questionnaire
    • 4.4.2. Database Mining
    • 4.4.3. Exit Interviews
    • 4.5. DATA ANALYSIS
      • 4.5.1. Assumptions
      • 4.5.2. Descriptive Statistics
      • 4.5.3. Factor Analysis
      • 4.5.4. Internal Consistency Reliability
      • 4.5.5. Predictive Validity
    • 4.6. MISSING DATA
    • 4.7. DEFINITION OF KEY VARIABLES
      • 4.7.1. Retention
      • 4.7.2. Withdrawal
      • 4.7.3. Academic Success
      • 4.7.4. Non-Cognitive Variables
    • 4.8. LIMITATIONS
    • 4.9. CONCLUSION
  • CHAPTER 5 RESULTS
    • 5.1. INTRODUCTION
    • 5.2. DESCRIPTION OF THE SAMPLE
    • 5.3. FACTOR ANALYSIS
    • 5.4. SCALE RELIABILITY
    • 5.4.1. Cronbach’s Coefficient Alpha
    • 5.4.2. Spearman Brown Formula
    • 5.5. DESCRIPTIVE STATISTICS OF THE FACTORS
    • 5.6. TEST OF NORMALITY
    • 5.7. SPEARMAN CORRELATION COEFFICIENTS
    • 5.8. CROSS-TABULATIONS
    • 5.9. RISK FOR FAILURE PREDICTION MODEL
      • 5.9.1. Multiway Frequency Analysis
      • 5.9.2. Multiple Regression Analysis
      • 5.9.3. Tree-analysis of the Academic Readiness Questionnaire Factors
      • 5.9.4. Tree-analysis of the Academic Readiness Questionnaire Items
    • 5.10. RISK FOR WITHDRAWAL PREDICTION MODEL
      • 5.10.1. Multiway Frequency Analysis
      • 5.10.2. Binary Logistic Regression Analysis
      • 5.10.3. Tree-analysis (CHAID)
    • 5.11. EXIT INTERVIEWS
    • 5.11.1. Reasons for Withdrawal and Sub-reasons Contributing to Withdrawal
    • 5.11.2. Major Influences on Studies
    • 5.12. CONCLUSION
  • CHAPTER 6 INTERPRETATION
    • 6.1. INTRODUCTION
    • 6.2. PREDICTING RISK FOR FAILURE
    • 6.2.1. The Influence of Racial Background and Language
    • 6.2.2. The Influence of High School Achievement
    • 6.2.3. The Influence of Credits Registered
    • 6.2.4. The Influence of Goal Orientation
    • 6.2.5. The Influence of Learning-efficacy
    • 6.2.6. The Influence of Gender
    • 6.2.7. The Influence of Distance of High School
    • 6.2.8. The Influence of Parental Education at the University of Pretoria
    • 6.2.9. The Influence of Reading Behaviour
    • 6.3. PREDICTING RISK FOR WITHDRAWAL
      • 6.3.1. The Influence of Racial Background and Language
      • 6.3.2. The Influence of High School Achievement
      • 6.3.3. The Influence of Credit Registered
      • 6.3.4. The Influence of Reading Behaviour
    • 6.4. EXIT INTERVIEWS
    • 6.4.1. Scope of Withdrawal
    • 6.5. STANDARDISATION OF THE ACADEMIC READINESS QUESTIONNAIRE
    • 6.5.1. Reliability
    • 6.5.2. Validity
    • 6.5.3. Bias in Predictive Validity
    • 6.6. CONCLUSION
  • CHAPTER CONCLUSION AND RECOMMENDATIONS
    • 7.1. TESTING THE HYPOTHESES
    • 7.2. SUMMARY OF A READINESS AND RETENTION MODEL
    • 7.3. CONCLUDING REMARKS
    • 7.4. CONTRIBUTION OF THE STUDY
    • 7.5. RECOMMENDATIONS
    • REFERENCES
    • APPENDIX A
    • APPENDIX B
    • APPENDIX C

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Students’ readiness for university education

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