My name is Dr. Christopher Moore, and in this video I will share the plans for a new short course template design for building AI competence.

There is a high demand for AI literacy and competency for all UOW staff and students in using AI tools in ethical, responsible, critical, and creative ways. Each industry, sector, profession, and career will change as AI tools augment how we work, produce, learn, and communicate. How are you going to be implementing these tools in your work, your teaching, and your research?

To test our template design, we will produce an open access two credit point micro-credential on AI image generation. We are an interdisciplinary team from the faculty of Arts, Social Sciences, and Humanities. We want to help staff and students learn about visual communication and the creative expression enabled by generative AI tools through skill acquisition and responsible application.

AI image generation tools will be relevant to all UOW staff for analyzing and visualizing research data, communicating with students, and engaging with internal and external audiences. Developing your AI competence will support your effectiveness in these roles. We have the opportunity to ensure that all UOW students can graduate with critical and creative AI readiness, literacy and competence.

The short course will have a practical focus and provide collaborative work integrated learning experiences for, future students. We intend that the short course be a pathway to university for high school students. The broader public professionals, business operators and so on be able to turn to UOW to develop their AI competence through this course.

Our template design will feature three modules. The first module will be on the ethical and legal use of AI tools involving formative tasks on developing critical thinking around issues like cultural sensitivities and intellectual property laws. The second module will focus on expanding critical perspectives of AI tool use and creative thinking when it comes to visual communication. The final module will be on the professional presentation and the development of practical skills.

The project will involve staff and current students in its design and testing phases, resulting in both the short course and resources available to staff via the LTC Learning hub. To finalise the microcredentials participants will enroll in a one day workshop involving a professional challenge with industry experts, either online or on campus.

Whether you're a climate scientist, a chemical engineer, a social media manager, a subject coordinator, or a classroom tutor, AI competence will be a core component of your professional skills in the future. With our short course design template and the initiation of these lifelong learning opportunities, UOW will be a leader in AI learning and teaching.

Thank you for watching.

Yulungah Welcome, Mauya

The title of the project that we are proposing, is addressing the global, disconnection from country lend and, place, through decolonized assessment, practices. Our team, is made up of, academics, in social work and other disciplines who are interested in, de centering current pedagogy around assessments.

So why we decolonizing assessment practices? Why is it important?

I think one of the reasons is many of our educators as well as students, they come from cultures that are collectivistic and, their values practices are not always reflected in, western, individualistic ways of, assessing, achievement. And, and therefore, I think there are ways, other ways to envision assessment.

Same for me as well. I come very much from a framework of working collectively, of working with community, working together, and I think that we as educators can fall into that individualistic singular way of teaching and learning and assessments. And I think it's exciting to think outside the square and look at a broader range of assessment practices that encompasses that whole collective framework and narrative.

And, and I like the fact that we've both talked about, collective approaches.

Mm-hmm.

Yeah.

And that's what we're trying to do. The assessment is we do it in that collective, instead of just based on that individual competitiveness.

Mm-hmm.

It's how can we work collectively and bring that culture back of working together. And we spoke about that the other day of that, that whole group dynamic. How do we decolonize the group dynamic? And also how do we decolonize how we see the knowledge that they're sharing? So our judgment, our, our understanding of what they learned, we also need to, to reflect on and, and decolonize.

That's right. And so going on that collective model and that organic way of working together, we are gonna think about that in the whole project. We are gonna work with our, our community and our partners and, to come up with a Moodle site that actually works for educators to look at how to decolonize not only the design of their assessments, but also the moderation process and the marking of that, which we know students really feel challenged by it lots of times. We're also gonna then evaluate, we're gonna come up with a few different assessments that are decolonized, from the word go from the beginning. And then we're gonna do an evaluation that organically is created throughout the process of this group in order to really make sure that what we are creating works for both our educators and students across the board.

Thank you so much.

Thank you.

Thank you.

So we want you to think of a subject at uni or high school that you really enjoyed. Maybe it was the topic area that was what piqued your interest, but what would've kept you engaged was usually the way it was delivered, whether the academic was particularly inspiring, whether the materials or technology they used were what got you interested and involved. This is really at the core of our project, and so our project is about trying to think about how we engage our students through class participation as an assessable item.

The school of law at the University of Wollongong has prided itself over the last 30 years on its what to us seems normal, but is now called flip classroom or Socratic method. The idea of engaging students and monitoring and measuring and assessing their engagement.

So the significance of this project is to provide a scaffold or a best practice approach to conducting assessments that involve class participation and student engagement that also recognizes the differences in student learning and provides them with equitable approaches to their different learning styles.

So how are we going to develop this best practice model? We are really interested in hearing from our students about what makes the most effective, engaging learning environment for them. We would also love to hear from some of our most innovative academics about their teaching practices that inspire and motivate our students, and we'll also canvas some of the literature in the area to help develop this model quality assessment tool.

In the end, the short-term goals of this project would be to create assessment, rubrics, tools, drawing on a range of technologies that provide for assessment of class participation that is consistent, transparent, and equitable for all our students, leading ultimately to student engagement, student satisfaction, and student retention.

Big picture though, really, we are all about developing communication skills, which is essential employability skills for our future graduates.

Hi everyone. My name is Oleg Yerokhin I'm a senior lecturer at the Discipline of Economics. And in the, in this video, I would like to talk about my proposal called Leveraging Generative AI to deliver student feedback.

So we know that feedback is very important in the learning process. When you learn a new concept or idea, you would like to test it out and see if you understood correctly, and this gives you confidence to move forward and motivates you to study more. Unfortunately, when we teach large classes such as first year classes in the faculty of business, they usually involve hundreds and hundreds of students. So the issue of timely and constructive feedback on formative assessments is, we find it very challenging.

Now, as you know, the teaching landscape, has changed dramatically at the beginning of this year when the large language models became publicly available. So now we find ourselves in a situation where students routinely use this models for obtaining feedback and completing assessments. And while in general, this is very beneficial for students, there are a couple of issues with this development.

So, from my point of view and my experience of teaching in this environment, I see two major challenges posed by the large language models. So oftentimes, while they're perceived very credible, as very credible source by students, they deliver incomplete or outright incorrect answers. And second, they deliver these answers as given without trying to encourage the students to learn the material itself. So this is not optimal from the pedagogical point of view.

So in this project, I'm proposing to address these challenges by taking control of the model output using prompt engineering techniques. So essentially the project is about building an AI based tutor who would deliver factually correct and pedagogically sound feedback to formative assessments.

So the purpose of the AI tutor would be to take, a given question such as, for example, a question about inflation, which is administered at the end of the lecture to test students understanding of the material, the student or user will input their answer and crucially, along with the user's answer the following information will be transmitted to the model via, via API call. So the correct answer so that we eliminate the problem of model giving superiors or incorrect answers. And the so-called system prompt, which tells the model how to behave. So we tell the model that they are a capable and friendly economics tutor and they deliver feedback in a certain way.

So there is not enough time in this speech video to discuss the IT tutor model in detail. But what I did, I build a prototype app, which is fully functional. It contains only five questions, but it is connected to the API. It gives feedback, which is factually correct, and it uses appropriate pedagogical strategy. So feel free to go to this, URL and test it out and see how, the tutor that I'm proposing will work in practice.

My name is Dr. Sasha Nikolic. Using AI, we plan to help students develop the knowledge and skills they need in technical numerical based subjects, reducing the high dropout rate across engineering due to its difficulty.

If we can transform the learning experience for just one student, the expense of the grant would be reversed. This project can support UOW goals. Should this project be successful, it will provide students with access to innovative educational experiences that prepares students for the future of work.

The university has many existing support services in place. UOW does provide students with access to 24/7 support for services. But unfortunately, this does not include access to support related to the technical components that make up the majority of the engineering degree.

This project builds upon the team leader's first high-impact study of AI on education. One opportunity of greatest impact is to use AI to provide 24/7 learning support. However, our study highlighted that accuracy was a major risk. This work aims to test if and how AI can be used to provide students with flexible and reliable support in conjunction with structured learning pathways.

The first step is to work out what type of prompting would be best suited to enable AI self tutoring. As you can see on the screen, our preliminary work confirms the potential. In this study. We need to investigate and confirm how interactive it can be. How well can it guide the student through examples? Can you determine student weak spots and concentrate on turning the situation around?

The second step is to work out which technology from free to paid can provide reliable support that students need. Our holistic approach will look across the spectrum of knowledge required across the engineering curriculum, connecting 11 engineering majors. Not only that, but the diversity, breadth, and depth of the team will result in findings that will provide insights valuable for technical subjects across the world.

Core to the study is for the team to explore the educational benefits. Some team members are highly concerned of AI's impact on education. While others are optimistic, this is reflective of the university sector. Therefore, this study will also determine the staff acceptance of the strengths and risks associated with AI tutoring for firsthand experience.

Likewise, we will gain insights as to whether students, especially those struggling, we'll see the benefits and adapt to this technology. This project can revolutionise the support given to technical subjects. It can support UOW's goals and transform the student learning experience.

Hello everyone, this is Jack Yang from the Centre for Artificial Intelligence and today this is my pleasure to introduce our project on behalf of our centre.

Well, this project is called AI4U enhancing AI competency for UOW non-Computer Science Community. Well, in today's job market, there is a growing demand for AI skills. According to a 2022 linking survey, major consulting firms now require more computer science students than those with accounting backgrounds. These, in fact, create challenges for non-CS individuals who want to learn AI, and we recognise this increasing need for people from diverse academic backgrounds to obtain variable AI knowledge and skills to boost lay readiness for the job market.

Accordingly, our project AI4U is exactly designed to offer a online self-paced AI learning program exactly targeted on those non-CS academic staff and students.

Well, our program will offer four modules including contemporary, AI and machine learning, deep learning, natural language processing, and generative artificial intelligence for topics. Alongside our learning program, we will also provide the multimedia materials, interactive assessments to check participant's progress to facilitate their learning experience.

We will, of course, issue certificates upon meeting minimum requirements from our centre of AI. We'll also collaborate with faculty leadership to explore credit integration possibilities. For the sustainability of this proposal, our centre for AI remains dedicated to advancing AI education using existing teaching expertise and the materials from our projects and, a series of short courses we had on 2022.

Our centre, for AI is also commit to ongoing website maintenance and the material updates leveraging our in-house AI expertise and skills while keeping cost minimum.

Well, that's all everyone, from the time being more details about our program can be found in our proposal, and I appreciate your time and attention and looking forward to work with you very soon.

Thank you very much.

Hi, I'm Lloyd White from the School of Earth, atmospheric and Life Sciences within the faculty of SMAH, and this proposal is to try to develop an automated approach to mapping our curriculum, not just within our school, but ultimately to develop this tool that could be rolled out across the university.

The context of this is that for the past five years or so, course teams in SMAH have been following a fairly laborious approach of, mapping out key bits of information in their degrees. And this base, this approach basically follows, subject coordinators entering key bits of information, about what skills, are in their subjects assessment tasks, and entering all of this information into a Word document that an Academic Program Director will then extract that information and put it into a spreadsheet where it can then be, interrogated, through making plots and figures, which try to summarise, bits of information a little bit more.

So we've been using this approach to look at our assessment tasks, to look at, how well our degrees, scaffold, from first to third year where there's, where there's overlaps and gaps in our, in our majors, and ultimately, this is a fairly slow task, and, because it's so slow, it means that we can't really do it, every year. So we're doing it every, every few years, and what we're trying to do is develop a way that we can automate this.

So we think that there's a way that we can extract information from COSMOS where a lot of this information already exists and, develop a program that can automatically, read and extract that and, and plot that information that we want, so we can make decisions, faster and we can improve our, our teaching, programs, much more faster. So ultimately, this will benefit students and the student experience where we can identify overlaps and, identify where there's repetition is occurring between subjects and, rectify that, much faster than we would otherwise do.

You'll see if you look at the bottom of our application, that there is, some screenshots showing the examples of what we have been doing for, there's Word document templates and Excel spreadsheets. And, that'll give you an idea of how long things take, but otherwise we're hoping that our project team within SMAH and Future Ed can develop this tool and then roll it out across the university.

Thank you.

Hi, I am Russell and on behalf of our team, we're putting together a Learning Teaching Grant.

So our three main problems are over subscription of the anatomy lab. We have overuse of cadavers, which means that we have a poorer cadaveric experience for second, third, and postgraduate students. We also have no room for growth in the anatomy subjects themselves.

Our second problem is we have current assessments which are not fit for purpose, so they're not assessing deeper learning. We're sort of just relying on students to have a recall and a rote learning, type of memory where there's no integration of the concepts and there's very limited critical thinking, which is what universities are about.

The third problem is you have students aren't being adequately equipped in the digital literacies. So when they're moving out into their career paths, they're moving out without this digital literacy.

So through this Learning and Teaching Innovation Grant, we plan to address these problems in three ways. Transform our anatomy curriculum, so by providing quality anatomy assessments and the blended learning modules by implementing Anatomage and other 3D learning capabilities. Two, build capacity for student growth by creating a blended learning environment and decreasing the pressure on the anatomy lab. And three, to modernise and enrich the student learning experience. So make it engaging, making it interactive, hands-on, building digital literacy, and also improving 3D spacial awareness.

So we'll do this in three ways. One, we'll create two blended learning modules for incorporating into large, large first year subjects and into equivalent small cohort run by UOW College. We'll make this process robust by bringing on board students as partners. With a co-design approach, this means that we are engaging all stakeholders involved from the get go. We are collaborating with experts in digital neuroanatomy from Swinburne, University of Technology to achieve this same. Two, we'll create a quality, authentic assessment that's scalable from large to small cohorts. And three, using mixed methods or gain perspectives of students' experience in using digital and anatomy technologies.