In this workshop, Professor Grayson will introduce systems thinking, systems design and systemic change, illustrated with examples from Wits related to how they developed and are implementing the Wits Institutional Framework for Student Success.

Four universities will then present their work on developing their own institutional student success feedback, followed by time for questions and suggestions from other workshop participants.

The workshop will conclude with a summary of ideas and challenges raised during the workshop and suggestions for how to make further progress along the road to promoting student success.

Presentation by Diane Grayson

The discussions will be framed around:

1. Understanding the concept of Student Agency
2. Identifying the factors that hinder Student Agency
3. What Universities can do to encourage and promote Student Agency
4. How student agency can lead to student success
5. Sharing students’ perceptions on how to include and promote Student Agency

The outcome of the workshop: A better understanding of student agency in the South African context and how best to encourage inclusivity of students, and thereby promote co-creation of successful educational experiences.

The Siyaphumelela Western Cape Regional Network invites you to participate in this, the second workshop on sustainable, collaborative approaches to open textbook production that support innovative pedagogical practice and open new pathways for student co-creation.

This session will introduce participants to practical ways in which to initiate open textbook production and engage students in authorship, quality assurance and publishing processes.

The two workshops will introduce you to some of the most widely used predictive modelling techniques and their core principles. By attending this workshop, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data.

After successfully completing the two workshops, participants should be able to:

• Understand how to use predictive modelling for student success
• Source data from different files
• Clean missing values, transform and prepare data
• Model building-build, train a basic model
• Test for model accuracy
• Make predictions and score predictive models
• Build dashboard for the predictive model.

Workshop outcomes

This workshop will introduce you to some of the most widely used predictive modelling techniques and their core principles. By attending this workshop, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data.

After successfully completing the two workshops, participants should be able to:

• Understand how to use predictive modelling for student success
• Source data from different files
• Clean missing values, transform and prepare data
• Model building-build, train a basic model
• Test for model accuracy
• Make predictions and score predictive models
• Build dashboard for the predictive model.

When implementing an Improvement Science framework in the context of Higher Education, performance challenges at multiple scales must be considered. At the whole-institution scale, the overall graduation rate is a metric which can be cascaded to the academic programme scale, where the causes of progression limitation are then evaluated. In turn, this cascades to the individual coursework level, where performance in assessments and even individual students is considered.

When such analysis yields insight into the potential causes, we then close the loop by designing interventions aimed at ameliorating the challenges identified. In this workshop we illustrate the implementation of such a framework through the AutoScholar Advisor system. In addition to the scale cascading and analysis for identifying causes of limitations, we propose interventions based on automated student advising and automated teaching and learning methods.

The integration with human-centred, non-automated methods is outlined together with access to methods which participants may evaluate both during and out of session.

Open textbooks are an important phenomenon in the global higher education landscape with compelling affordances around cost savings and content development approaches that address localisation and decolonisation of the curriculum.

Workshop 1: Introduction to open textbooks for social justice

This interactive session will provide an introduction to the concept of open textbooks, with a particular focus on the affordances they provide to address social justice in the classroom.

This Power BI intermediate workshop provides one notch up from the beginner’s course. Users will be able to enhance their knowledge on the 4 pillars of Power BI, that is: Data loading and transformation, Data modelling, DAX calculations, Reports and visualizations. That is, mastering complex data transformations, understanding the context of the data and using the Power of DAX to output valuable insights.

The various techniques will be demonstrated and applied to real-world data in a higher education setting. Participants will learn step-by-step how raw data can be transformed and developed to provide valuable insights that can drive decision making using Power BI.

This Power BI beginner workshop provides an overview and introduction to using Power BI as an analytical tool. The various techniques will be demonstrated and applied to real-world data in a higher education setting. Participants will learn step-by-step how raw data can be transformed and developed to provide valuable insights that can drive decision making using Power BI. This workshop will provide a detailed overview of the essential features of Power BI Desktop and Power BI online service. You will be guided through a step-by-step process on how to develop dynamic reports, following the 4 pillars of Power BI development: Data loading and transformation, Data modelling, DAX calculations, Reports and visualizations.

Text

• Brief history of SI

• Theoretical perspectives on SI

· Theories

· SI International definition & features

· Differences between SI, tutoring and mentoring

· Benefits of SI/ Peer Collaborative Learning

· SI desired outcomes

The Supplemental Instruction (SI) programme was created at the University of Missouri-Kansas City (UMKC) in the early 1970’s. The programme was developed in response to the high drop-out and failure rate in historically difficult courses, particularly for minority and under prepared students. The programme is based on the principles of peer-collaborative learning and the integration of learning skills in a course-specific rather than remedial setting.

SI at Nelson Mandela University

SI has been offered, first at the former University of Port Elizabeth and now at Nelson Mandela University since 1993.

This programme was selected by the University after a detailed survey of existing student academic development programmes both locally and abroad. The SI model was adopted because it was felt that it could meet the holistic needs of its students; it could be instituted campus wide; it was cost effective; and had a proven track record.

SI SUPERVISOR TRAINING

By the end of the training delegates will be able to:

Develop a SI programme for their context, implement, monitor, and evaluate the programme, and train SI Leaders. 

The name Supplemental Instruction is trademarked and may only be used in conjunction with the international recognised model of the programme.

Workshop format

For the convenience of delegates and to avoid online fatigue, the training is divided into four sessions.  Attendance of all four sessions are compulsory to receive the internationally recognised SI Supervisor Training Certificate.  With the certificate you may implement and manage a SI programme at the institution you are employed at and use the name Supplemental Instruction if the international model requirements are met.

The session held were as follows: 

• Session 1: 11 April 2022, 13:30-16:00 (What is SI?  History & Theoretical perspectives)
• Session 2: 12 April 2022, 09:00-11:30 (SI session facilitation and management)
• Session 3: 12 April 2022, 13:00-16:00 (SI programme implementation A – institutional preparation and planning)
• Session 4: 13 April 2022, 09:00-12:00 (SI programme implementation B – programme operations, management and evaluation)

This workshop focuses on the importance of understanding students and being responsive to diverse student profiles in our institutional designs. In understanding who our students are, we can design learning and support them accordingly and enhance the chances of students’ success.

During this session, findings from two key national reports will be synthesised and reflection and discussion on how we understand and make sense of students’ learning will be facilitated.

Watch the recorded session, that took place on the 7 April 2022, here:  https://youtu.be/MnRCeK7ferA

Diagnostic Assessment Series: Session 1 (24 November 2020)

Assessing strengths and weaknesses to inform the development of  wrap-around support

 Watch the recording of this session on our Youtube channel at https://youtu.be/892Z3pw09lM.

Diagnostic Assessment Series: Session 2 (16 March 2022)
The use of diagnostic instruments – Understanding the student profile

Introduction to the process, techniques, and principles of using diagnostic information. The webinar looks at the instruments that are used to collect this type of data to a) understand the instrument itself and b) understand the reports on results gathered with the instrument. The aim is to help participants make the necessary connections between the design of the instrument, the interpretation of results based on the instrument and what that means in terms of the student profile within their context. 

Watch the recorded webinar at https://youtu.be/Ta8PwuliicQ

Diagnostic Assessment Series: Session 3 (23 March 2022)
Responding to student needs – a data-driven approach

This session aims to assist participants in putting diagnostic information in conversation with curriculum. This session picks up where the previous session in this series left off and is focused on using the student profile, drawn from diagnostic information, as a basis for the development of curriculum interventions, changes in the curriculum itself, or even, pedagogy.

Participants who did not attend the previous sessions are strongly encouraged to watch the recordings of sessions one and two in preparation for this session and to share the necessary information for us to generate relevant cohort reports ahead of this session.

With a cohort’s profile as starting point, the CEA Team will help participants engage with artefacts from a particular course in an effort to understand the implications of what we have learnt about the needs of the students that will be enrolling for a given course.

Watch the recorded session here https://youtu.be/qR3R3V9QUPo

To understand module reviews through a Course Analytics framework and implement reviews using surveys or structured interviews; structure data to facilitate informed decisions; and close the module review-loop with the 'Theory of Change'.

Dr Juan-Claude Lemmens, Head Higher Education Research an Innovation at UP hosted this webinar which was targeted at professional support staff that plan to facilitate module reviews at their universities.

Objectives:

• Understand module reviews through a Course Analytics framework
• Implementing module reviews with a structured survey or interviews
• Understand how to structure data to facilitate data-informed decisions [to improve the quality of teaching and learning]
• Understand how to close the module review-loop with the “Theory of Change”

Watch the recorded session which took place on the 10th February 2022 here: https://youtu.be/Q26i9YVI3Ow