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Towards a Conceptual Model of Retention and Success in Distance Education: The Case of the University of South Africa P

Towards a Conceptual Model of Retention and Success in Distance Education: The Case of the University of South Africa Presented at the SAAIR Annual Forum Port Elizabeth, 21 September, 2009. Prof George Subotzky Executive Director: Information & Strategic Analysis University of South Africa.

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Towards a Conceptual Model of Retention and Success in Distance Education: The Case of the University of South Africa P

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  1. Towards a Conceptual Model of Retention and Success in Distance Education: • The Case of the University of South Africa Presented at the SAAIR Annual Forum Port Elizabeth, 21 September, 2009 Prof George Subotzky Executive Director: Information & Strategic Analysis University of South Africa

  2. Overview • Background & Context • Appropriate Measurement and Quantification of the Retention and Success Challenge at Unisa • Towards a (unique?) Conceptual Model for Distance Education Retention and Success

  3. Introduction • Retention and Success: key challenge for IR in relation to conference theme – closing the loop between: • Evidence & Practice • Theory & Practice • Organizational Learning & Transformation

  4. Background • Retention and Success a major focus of concern worldwide and, consequently, of IR internationally • A particular challenge at Unisa, given its institutional character as a distance education mega-university in the developing country, new democracy context of South Africa • Strong external imperative to improve retention and success rates from government outcomes-based funding and enrolment planning framework • Strong internal imperative: key focus in all institutional policy and planning documents • 2015 Strategic Plan • Recent Institutional Operational Plan Reviews • Recent QA Audit Reports: 3 cohort case studies conducted • Coordinated initiative through Throughput Forum as part of ODL development

  5. ODL – preferred business model for Unisa • Through blended learning and innovative application of technology, this focuses on bridging various kinds of distances between: • Student and institution (counseling, academic & administrative services) • Student and study materials (learner support) • Student and other students (social networks & community of scholarship) • Therefore, engagement central to ODL model

  6. University of South Africa: Quantifying the Retention & Success Challenge

  7. Key concerns • Appropriate measurement & benchmarks for success in DE Context • Part of bigger concern for regulatory environment to accommodate the characteristics & dynamics of DE

  8. Measuring Retention & Success • Two key elements: • Graduation rate: volume-based measure of efficiency • Time to completion: time-based measure of efficiency • Retention: 1-year rates – universal measure

  9. Benchmarking Time to Completion Two key characteristics of DE pertinent here • Underpreparedness (majority phenomenon) • Difficult to factor in accurately • Tinto (2008): uses time and a half benchmark in relation to study on low-income students in the US • Predominantly part-time study load • Average FTE:headcount ratio around 0.5 • Signals that on average Unisa students carry half a course load • Central claim: Expected minimum time to completion should be around double minimum time of qualification • Together: 3-year UG qualification = 7.5 years??

  10. South African Graduation, Dropout & In-process Rates by Institutional Type, 2000 Cohort Source: (Scott, et al, 2007)

  11. Unisa Cohort Dropout Rates, 2001-7

  12. Calculating expected minimum time ito study load • Course load indicated by FTE: headcount ratio • For example, for one of the three case studies, namely the 2007 B Com cohort, the calculation is as follows. This 3-year qualification had a FTE: headcount ratio of ,456 Expected minimum time = minimum time X 1 FTE: headcount ratio Expected minimum time = 3 years X 1 ,456 = 6,6 years

  13. Case studies: Sample • Cohorts in 3 UG qualifications • 3 largest qualifications within the main undergraduate degree qualification types chosen as follows: • General 1st Bachelor’s Degree (minimum duration 3 years): B Com • Professional 1st Bachelor’s Degree (minimum duration 3 years): B Compt • Professional 1st Bachelor’s Degree (minimum duration 4 years or longer): LLB

  14. 1st Case: B ComGraduation, Attrition & Retention Rates

  15. B Compt: Graduation, Attrition & Retention Rates

  16. LLB: Graduation, Attrition & Retention Rates

  17. B Com: Time to completion by year

  18. B Compt: Time to completion by year

  19. LLB: Time to completion by year

  20. B Com: % entering students dropping out by year

  21. B Compt: % entering students dropping out by year

  22. LLB: Proportion of Entering Students Stopping Out By Year

  23. Conclusion • Main Challenge: Reducing dropout as principal focus to improve retention and success • Time to completion satisfactory • Time to dropout and stopout indicate risk moments to be addressed through appropriate interventions

  24. University of South Africa: Towards a DE Retention & Success Model

  25. The UNISA Throughput Forum • Strong external and internal imperative to improve retention and success, especially in ODL context • Co-ordinated and integrated effort to improve retention and success • Approach adopted: to achieve the comprehensive understanding of all factors shaping retention and success through modeling initiative • Purpose of modeling initiative: to provide a systematic, evidence-based, contextually-relevant foundation to inform and guide initiatives to improve retention and success • This work undertaken by modeling Task Team

  26. 2-fold Framework for Enhancing Retention & Success • Comprehensive modelling initiative • Literature review (conducted by Dr Paul Prinsloo) • Drawing from this, the conceptual/hypothetical modelling of the positive and risk factors shaping the student experience, retention & success in the ODL context of Unisa (Modelling Task Team) • Together, the literature review and conceptual model released as a Strategic Discussion Forum discussion document during April for expert response, comprehensive engagement & feedback and then to STLSC & Senate, and at two international and one local conferences • Regarding the model, determining what variables are knowable, measurable, (is/may be) available and actionable • Utilising model to shape student tracking system, to gather relevant and available quantitative and comprehensive complementary qualitative data (myUnisa) • Statistical and analytic modelling to determine factors shaping success and to predict and address risk and readjusting the model as necessary

  27. A 2-fold framework for enhancing throughput & success • Transforming institutional identity, attributes & practices • Utilising consolidated findings (as actionable intelligence) to inform and guide existing and new Learner Support Framework and initiatives and academic practices and operational improvements in order to improve success, throughput and the student experience; • Monitoring and evaluatingthese initiatives over time as part of continuous reflection and improvement and ongoing QA

  28. MANAGEMENT OF STUDENT EXPERIENCE, RETENTION, SUCCESS & GRADUATENESS Shaped by modeling process Conceptual Modeling M & E Learner Support Interventions and other academic & administrative changes Identifying what is relevant, measurable, available & actionable Tracking System Statistical & Analytic Modelling producing Actionable Intelligence

  29. Overview of the literature review • The comprehensive review covered the literature from the earliest model proposed by Spady in 1970 to current theoretical developments 2. This included retention models • In international HE (Spady, Bean, Tinto, EPI) • In international distance education (Kember, Simpson) • In South Africa (REAP, Koen, CHE). • Theoretically, the models range from strictly sociological (Baird, Berger) to anthropological (Hurtado), social-critical (Tierney) and psychological (Bean and Eaton) 2

  30. Some pointers • Student retention is a complex, layered and dynamic set of events. • International models are not appropriate to the specific African, developing country and ODL context of Unisa. • In particular, they do not recognise need for institutional transformation – an especially prominent issue in SA HE policy. • Self-efficacy, attribution and locus of control are important constructs in explaining students’ academic and social trajectories (extrapolated in the model to explain institutional attributes as well).

  31. Some pointers • In an ODL context, non-cognitive and institutional factors may impact more on student success than in residential settings. • While important to identify relevant variables in the Unisa context, even more important will be to determine the combined effects of, and relationships between different variables at different points in the student journey. • Research into student retention and success should be quantitative and qualitative. • Relatively low proportion of retention variance explained by current statistical models • Complementary strategy: Obtain rich qualitative information as part of ‘thick’ student profiling and ongoing intensive 2-way engagement

  32. Key Constructs • Situated agents: student and institution • Historical, geographical and socio-cultural backgrounds • Capital • Habitus • Student Walk • Mutual engagement • With regard to academic & non-academic factors • Broad definition of success • Transformation process • Managing risks and opportunities • Domains: student – Intra-personal and inter-personal institution – academic, administrative & social • Modalities: attribution, locus of control, self-efficacy

  33. Key explanatory claims • Success broadly defined: • Fit at each stage of the student walk from pre-admission to participation in workplace & society • Includes course success, graduation & positive student experience • Success as the outcome of sufficient fit • Sufficient fit as the outcome of mutual transformation to ensure necessary preconditions • Mutual transformation as the outcome of mutual engagement • Mutual engagement as the outcome of mutual knowledge and co-responsibility

  34. SHAPING CONDITIONS: (predictable as well as uncertain) • Social structure, macro & meso shifts: globalisation, political economy, policy; National/local culture & climate • Personal /biographical micro shifts TRANSFORMED STUDENT IDENTITY & ATTRIBUTES: • STUDENT • IDENTITY & ATTRIBUTES: • Situated agent: SES, demographics • Capital: cultural, intellectual, emotional, attitudinal • Habitus: perceptions, dispositions, discourse, expectations • Domains: • Intra-personal • Inter-personal • Modalities: • Attribution • Locus of control • Self-efficacy • Processes: • Informed responsibility & ‘choice’ • Ontological/epistemological dev. • Managing risks/opportunities/ uncertainty: Integration, adaptation, socialisation & negotiation FIT FIT FIT FIT FIT FIT • THE STUDENT WALK: • Multiple, mutually constitutive interactions between student, institution & networks • Managing complexity/ uncertainty/ unpredictability/risks/opportunities • Institutional requirements known & mastered by student • Student known by institution through tracking, profiling & prediction Retention/Progression/Positive experience Success Choice, Admission Learning activities Course success Gradua-tion Employ-ment/ citizenship FIT FIT FIT FIT FIT FIT TRANSFORMED INSTITUTIONAL IDENTITY & ATTRIBUTES: • INSTITUTIONAL • IDENTITY & ATTRIBUTES: • Situated organisation: history, location, strategic identity, culture, demographics • Capital: cultural, intellectual, attitudinal • Habitus: perceptions, dispositions, discourse, expectations • Domains: • Academic • Operational • Social • Processes: • Informed responsibility & choice • Managing risks/opportunities: • Transformation, change management, org. learning, integration & adaptation • Modalities: • Attribution • Locus of control • Self-efficacy • SHAPING CONDITIONS: (predictable as well as uncertain) • Social structure, macro & meso shifts: globalisation, internationalisation, political economy, technology, social demand • HE/ODL trends, policy • Institutional biography & shifts; Strategy, business model & architecture, culture & climate, politics & power relations

  35. Proposition 1 Student success is broadly interpreted and indicated by course success, retention and reasonably quick progression through the main phases of the student walk, and ultimately successful graduation and effective participation in the labour market and/or citizenship. Success also incorporates a positive student experience as a result of student-centred service excellence and efficient operations provided by the institution.

  36. Proposition 2 Student success and positive experience is the outcome of sufficient fit between the identity and attributes of the student and the institution through all phases of student walk.

  37. Proposition 3 Fit arises when elements of the student and institutional identity and attributes (capital and habitus) are optimally aligned at each successive stage of the student walk. Fit at these various points is the outcome of the specific individual student and institutional preconditions.

  38. Proposition 4 In order for fit to arise at each successive stage of the student walk, relevant transformative changes in the identity and attributes of the student and the institution are required.

  39. Student & Institutional Transformation • Processes • Crucially dependent on relevant mutual actionable knowledge • This is an essential precondition in the management of risks, uncertainties and opportunities • Student: understanding institutional expectation & requirements & executing these • Institution: tracking, profiling, predicting relevant activities, risks & opportunities and adapting practices accordingly

  40. Institutional Transformation • The institution’s obligation is to continually reflect on its assumptions and practices not only in order to improve delivery but to eradicate hidden socio-economic and cultural barriers to equitable student access & success and thus to achieve the QA criterion of fitness to purpose • This captures the transformative approach, failing which the institution perpetuates the social reproduction of elites

  41. Proposition 5 The student walk comprises a series of multiple, mutually constitutive interactions between the situated student and the situated institution and between them and their various respective networks through all points of the walk (Articulation with ODL model)

  42. Proposition 6 The formation and transformation of student and institutional identity and attributes is continuously shaped by overarching conditions at the macro, meso and micro levels

  43. Conclusion Unisa: Integrated, comprehensive approachto addressing the imperative of improving success, throughput & student experience – modelling approach Literature Review: Rich field of enquiry, with interesting array of theoretical perspectives International models not appropriate to developing country ODL context and do not recognise imperative for institutional transformation Unique features of Unisa Model: Key constructs and propositions, especially the central component of the need for mutual knowledge, engagement & transformation on the part of both student and institution Evidence suggests that non-cognitive and institutional variables impact equally (if not more) on student retention and success The initial indications from the literature and the conceptual model, as well as the envisiged qualitative and quantitative actionable intelligence should provide the basis of a much more comprehensive understanding of the student experience, retention & success at Unisa: key area of IR On the basis of this, the risks facing students and the institution can be identified, predicted, monitored & proactively addressed In turn, this should provide an important basis for fulfilling the objectives of the ODL model by helping to bridge the various distances between the student and retention and success, as well as a positive student experience.

  44. Thank you! Professor George Subotzky Executive Director: Information & Strategic Analysis University of South Africa subotg@unisa.ac.za

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