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 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 Prof George Subotzky Executive Director: Information & Strategic Analysis University of South Africa

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

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

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

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

University of South Africa: Quantifying the Retention & Success Challenge

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

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

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?? Benchmarking Time to Completion

South African Graduation, Dropout & In-process Rates by Institutional Type, 2000 Cohort Institutional Type Graduated within 5 years Still registered after 5 years Left without graduating Universities (excluding Unisa)50%12%38% Unisa14%27%59% All universities38%17%45% Technikons (excluding TSA)32%10%58% Technikon SA2%12%85% All technikons23%11%66% All institutions30%14%56% Source: (Scott, et al, 2007)

Unisa Cohort Dropout Rates, CohortNY2Y3Y4Y5Y6Y7Y , %54.8%60.9%62.4%63.5%64.4%65.0% , %61.9%65.1%66.9%68.4%69.6% , %59.3%63.6%66.6%69.0% , %49.8%56.8%61.4% , %51.5%60.3% , %59.7% , %

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 Calculating expected minimum time ito study load Expected minimum time = minimum time X 1 FTE: headcount ratio Expected minimum time = minimum time X 1 FTE: headcount ratio Expected minimum time = 3 years X 1,456 = 6,6 years Expected minimum time = 3 years X 1,456 = 6,6 years

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

1 st Case: B Com Graduation, Attrition & Retention Rates Cohort Year Entering Students GraduatesDropouts/TransfersIn process No% Average Time (Years) No% Average Time (Years) No% Average Time (Years) ,3%5, ,6%2, ,2%7, ,0%5, ,7%2, ,3%7, ,0%5, ,5%2, ,5%6, ,8%4, ,5%2, ,7%5, ,8%4, ,7%2, ,5%5, ,1%4, ,8%1, ,2%4, ,4%3, ,9%1, ,7%3, ,7%2, ,7%1, ,6%2, ,1%1, ,1%1, ,8%2, ,0%1, ,0 % 1,00

B Compt: Graduation, Attrition & Retention Rates Cohort Year Number of Entering Students GraduatesDropouts/TransfersIn process No% Average Time (Years) No% Average Time (Years) No% Avera ge Time (Years) ,4%4, ,5%2, ,1%8, ,5%4, ,8%2, ,8%7, ,1%4, ,0%2, ,8%6, ,8%4, ,6%2, ,6%6, ,0%4, ,4%2, ,6%5, ,2%3, ,3%1, ,5%4, ,8%3, ,0%1, ,1%3, ,6%2, ,9%1, ,5%2, ,4%1, ,0%1, ,5%2, ,0%1,00

LLB: Graduation, Attrition & Retention Rates Cohort Year Number of Entering Students GraduatesDropouts/TransfersIn process No% Average Time (Years) No% Average Time (Years) No% Average Time (Years) ,1%3, %2, %7, ,5%4, %2, %7, ,0%4, %2, %6, ,4%4, %2, %5, ,3%4, %2, %5, ,9%3, %1, %4, ,0%3, %1, %3, ,6%2, %1, %2, ,0%2, %1, %2, ,0%1, %1,00

B Com: Time to completion by year

B Compt: Time to completion by year

LLB: Time to completion by year

B Com: % entering students dropping out by year

B Compt: % entering students dropping out by year

LLB: Proportion of Entering Students Stopping Out By Year

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

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

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

2-fold Framework for Enhancing Retention & Success 1.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

A 2-fold framework for enhancing throughput & success 2.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 evaluating these initiatives over time as part of continuous reflection and improvement and ongoing QA

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

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). 3.Theoretically, the models range from strictly sociological (Baird, Berger) to anthropological (Hurtado), social-critical (Tierney) and psychological (Bean and Eaton) Overview of the literature review

30 1.Student retention is a complex, layered and dynamic set of events. 2.International models are not appropriate to the specific African, developing country and ODL context of Unisa. 3.In particular, they do not recognise need for institutional transformation – an especially prominent issue in SA HE policy. 4.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). Some pointers

31 5.In an ODL context, non-cognitive and institutional factors may impact more on student success than in residential settings. 6.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. 7.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 Some pointers

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

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

Processes: Informed responsibility & ‘choice’ Ontological/epistemological dev. Managing risks/opportunities/ uncertainty: Integration, adaptation, socialisation & negotiation Processes: Informed responsibility & ‘choice’ Ontological/epistemological dev. Managing risks/opportunities/ uncertainty: Integration, adaptation, socialisation & negotiation Domains: Intra- personal Inter- personal Domains: Intra- personal Inter- personal Modalities: Attribution Locus of control Self- efficacy Modalities: Attribution Locus of control Self- efficacy Processes: Informed responsibility & choice Managing risks/opportunities: Transformation, change management, org. learning, integration & adaptation Processes: Informed responsibility & choice Managing risks/opportunities: Transformation, change management, org. learning, integration & adaptation Modalities: Attribution Locus of control Self- efficacy Modalities: Attribution Locus of control Self- efficacy Domains: Academic Operational Social Domains: Academic Operational Social TRANSFORMED INSTITUTIONAL IDENTITY & ATTRIBUTES: STUDENT IDENTITY & ATTRIBUTES: Situated agent: SES, demographics Capital: cultural, intellectual, emotional, attitudinal Habitus: perceptions, dispositions, discourse, expectations STUDENT IDENTITY & ATTRIBUTES: Situated agent: SES, demographics Capital: cultural, intellectual, emotional, attitudinal Habitus: perceptions, dispositions, discourse, expectations Success INSTITUTIONAL IDENTITY & ATTRIBUTES: Situated organisation: history, location, strategic identity, culture, demographics Capital: cultural, intellectual, attitudinal Habitus: perceptions, dispositions, discourse, expectations INSTITUTIONAL IDENTITY & ATTRIBUTES: Situated organisation: history, location, strategic identity, culture, demographics Capital: cultural, intellectual, attitudinal Habitus: perceptions, dispositions, discourse, expectations SHAPING CONDITIONS: (predictable as well as uncertain) Social structure, macro & meso shifts: globalisation, political economy, policy; National/local culture & climate Personal /biographical micro shifts SHAPING CONDITIONS: (predictable as well as uncertain) Social structure, macro & meso shifts: globalisation, political economy, policy; National/local culture & climate Personal /biographical micro shifts 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 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 Choice, Admission Learning activities Course success Course success Gradua- tion 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 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 FITFIT FITFIT FIT FITFIT FITFIT Employ- ment/ citizenship Employ- ment/ citizenship TRANSFORMED STUDENT IDENTITY & ATTRIBUTES: FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT FITFIT Retention/Progression/Positive experience

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.

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.

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.

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.

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

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

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)

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

1.Unisa: Integrated, comprehensive approach to addressing the imperative of improving success, throughput & student experience – modelling approach 2.Literature Review: Rich field of enquiry, with interesting array of theoretical perspectives 3.International models not appropriate to developing country ODL context and do not recognise imperative for institutional transformation 4.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 5.Evidence suggests that non-cognitive and institutional variables impact equally (if not more) on student retention and success 6.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 7.On the basis of this, the risks facing students and the institution can be identified, predicted, monitored & proactively addressed 8.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. Conclusion

Thank you! Professor George Subotzky Executive Director: Information & Strategic Analysis University of South Africa