Explaining the variables effects of Supplemental Instruction (SI) on student outcomes in a Historical Disadvantaged Institution (HDI) Vuyelwa Dondolo Vuyisile Nkonki Khanyisa Mabece

Introduction and Context Peer Assisted Student Services are used all over the world PASS assist students with courses content and other relevant skills that will form an all rounded student UFH has two PASS programmes: SI and LWAP Identifying a high risk course

Introduction and Background Defining HDI: Higher Education South Africa (HESA) (2012) has labelled an HDI as the institutions that were oppressed by the previous Apartheid government based on languages and societal factors UFH is one of the listed HDIs (Barnes, 2012) UFH consists of 3 campuses: Alice (Main), Bisho (Extended) and East London. This particular study focused on the Alice campus, also considered a rural town. Differences between SI sessions and Tutorials in the UFH context

Differences between SI and Tutorials SI sessions Tutorials Targets at risks courses Small Groups Active Learning Voluntary Leadership Role Students participate in their own learning Students are free to ask questions when they want/need to Student set the agenda Large Classes Passive Learning Marks are given for attending and completing tasks Authority Figure Students are feel little investment in the process (spectators) Students are told what will be discussed or done in the tutorial

Follow up from Dondolo and Nkonki (2015) paper Focused on First Year students’ perceptions of the Supplemental Instruction programme This study found that the experiences of students with facilitation of the SI sessions, and their expectations of the SI programme, influence and shape their perceptions of the SI programme. Various perceptions are explained by expectations and preferences with respect to the focus of SI, and SI leaders’ facilitation methods.

Research questions What is the confluence of the selected explanatory variables on the effectiveness of SI on students’ outcomes in an HDI? Which explanatory variables bear on (or influence) the effectiveness of SI on selected students’ outcomes? Arising out of the findings, what SI model is suggested and can be developed?

Research methodology Quantitative approach Survey research design Convenience sampling Structured and closed ended questionnaire A sample of 122= 1st (4.1%) 2nd (77%), 3rd (13.1) and 4th (4.9%) year students. These students have attended SI sessions in the previous years and currently. Data was captured using SPSS and data was analysed using the ordinal regressions statistics.

Sections of the questionnaire 1. Biographical information (Faculty, Number of modules, current year of study) 2. Explanatory variables on the effectiveness of SI (11 variables). 3. Effects of SI on students’ outcomes (7 variables)

Explanatory Variables on the Effectiveness of Supplemental Instruction SI leaders’ facilitation methods; Lecturer’s attitude towards SI; Scheduling of SI sessions; Monitoring of SI attendance by the lecturer; SI leader-student relationship; Space for collaboration and transactional learning in the SI venues; Engagement, sharing, and exchange of ideas in the sessions; Follow-up and tracking of progress by SI leaders; Focus on the mastery of subject contents in the SI sessions; Encouragement to attend SI sessions by classmates; Accommodation of individual learning needs in the SI sessions.

Effects of Supplemental Instruction on students’ outcomes Acquisition of academic literacies; Improvement of marks in the assessment tasks; Unlock, expose and unpack difficult areas in the subject contents; Sense of community and belonging; Assimilation into the culture and ethos of the university; Acquisition of study skills; Development of graduate attributes).  

DATA ANALYSIS This inferential study involved more than one predictor variables (11 explanatory variables on the effectiveness of Supplemental Instruction) which were studied to explain variability in the outcome variables (Effects of Supplemental Instruction on 7 students’ outcomes). Thus, ordinal regressions were used. The researchers sought to identify which one factor or combination of factors best explained variance on the effects of Supplemental Instruction on selected students’ outcomes. Regression is a useful tool to analyse the relationship between multiple explanatory variables and outcome variables. Chen and Hughes (2004:2) maintain that if researchers wish to study the effects of explanatory variables on all levels of the ordered categorical outcomes, an ordinal regression method is more appropriate for valid results. In this instance, both the explanatory variables and the outcomes variables were ordinal scales. 

Data Analysis continued… The pseudo R-square indicates the proportion of the total variation in the response that is explained by the model (Cox and Snell, Nagelkerke, McFadden) The Pearson Chi-square indicates the data-model fit or consistency between observed data and estimated values.

Results Acquisition of academic literacies and competencies such as scientific reading and writing as a result of attendance to the SI sessions Pseudo R-square with Nagelkerke (.581) suggested that 58.1 percent variation in the response is explained by the model SILs’ facilitation methods that enhanced understanding of concepts; Scheduling of SI sessions that ensured availability and accessibility of the students The monitoring of SI attendance by lecturers SILs’ following up and keeping track of progress and performance also significantly explained this outcome. The Pearson Chi-Square (X² = 320.071 with d.f. of 284 and p = .069) showed consistency between observed data and estimated values (adequate model-data fit).

Results continued… Improvement of marks for the various assessment tasks (assignments, tests and examinations) as a result of attendance to the SI sessions The pseudo R-square with Nagelkerke (.824) suggested that 82.4 percent of the total variations in response explained SILs’ facilitation methods that enhanced understanding of concepts. To a limited extent lecturers’ attitudes towards SI fostered attendance to the SI sessions. Peer collaboration and transactional learning in the SI session venues is also associated to a limited extent with this outcome. The influence of classmates towards attendance of SI sessions was negatively associated with the improvement of marks. Accomodation of individuals’ learning needs in the SI sessions was to a limited extent also associated with improvement of marks. The Pearson Chi-Square (X² = 237.718 with d.f. of 284 and p = .979) showed consistency between observed data and estimated values.

Results continued… The sessions unlocked, exposed and unpacked difficult areas in the content subjects 59.8 percent of the variations in response explained SILs’ facilitation methods that enhanced understanding of concepts (). Lecturers’ attitudes towards SI which fostered attendance of the SI sessions (). Negative relationships with the monitoring of SI attendance by lecturers encouraged attendance to the SI sessions (). SIL relationship with students (), Peer collaboration and transactional learning in the SI session venues (). The focus of SI on the mastery of contents () and Accommodation of individuals’ learning needs in the SI sessions () The Pearson Chi-Square (X² = 178.323 with d.f. of 284 and p = 1.000) showed consistency between observed data and estimated values.

Results continued… The SI sessions offered a sense of community and belonging to the discipline and the university The Nagelkerke (0.516) suggested that 51, 6 percent of the variations in response explained SIL’s facilitation methods enhanced understanding of concepts. The monitoring of SI attendance by lecturers encouraged attendance of SI sessions The student-SI leader relationship created an atmosphere conducive for learning. Peer collaboration and transactional learning in the SI session venues. The negative association with encouragement by classmates to attend SI sessions suggested that this variable was influential to a limited extent. The significance of the test with Pearson chi-square (X² = 205.466 with d.f. of 275 and p = .999) showed consistency between observed data and estimated values.

Results continued… SI attendance enabled assimilation into the culture and ethos of the university 47.4 percent of the total variations in response explained. Significant influences: SI leader’s facilitation methods to a great extent. The negative association with monitoring of SI attendance by the lecturer suggested this variable was to a small extent influencing this outcome. The follow-up and tracking of progress and performance by SI leaders. The monitoring of SI attendance by the lecturer was negatively associated with this outcome signaling the limited influence of this variable. (X² = 251.684 with d.f. of 266 and p = .727) showed consistency between observed data and estimated values.

Results continued… Attendance in the SI sessions enabled acquisition of study skills The Nagelkerke (.674) suggested that 67.4 percent of the responses influenced significantly by: SI leaders’ facilitation methods; Peer collaboration and transactional learning in the SI session venues; Engagement, sharing and exchange of ideas in the SI sessions; Follow-up and tracking of progress and performance by SI leaders; Accommodation of individual learning needs in the SI sessions. (X² = 236.608 with d.f. of 284 and p = .981) showed consistency between observed data and estimated values.

Results continued… SI sessions developed graduate attributes such as responsibility, independent learning, self-monitoring, et cetera. 74.1 percent of the variations with Nagelkerke (.741) significantly influenced by: Lecturers’ attitudes towards SI fostering attendance; Positive influence of peer collaboration and transactional learning in the SI venues ; Negative association with engagement, sharing and exchange of ideas in the SI sessions; Follow-up and tracking of progress and performance by SI leaders. (X² = 158.980 with d.f. of 284 and p = 1.000) showed consistency between observed data and estimated values.

Conclusion Model and the data collected show more focus and bias towards academic and less on social integration. It would seem that the improvement of marks, development of graduate attributes, acquisition of study skills, SI sessions unlocked, exposed and unpacked difficult areas in the contents, and acquisition of academic literacies and competencies are students’ educational outcomes where SI is mot effective. The less successful outcomes areas on the sense of community and belonging to the discipline and the university suggest that the SI programme had less emphasis on these.

Recommendations Areas of success with high percentages in the model need to be consolidated Areas of less successful outcomes as indicated by lower percentages are niches for intervention Need to striking a balance between the academic and the social aspects of an all rounded student in the SI programme. The SI programme and the SI training should endeavour to focus more on the social and the emotional aspects of the students.

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