Yeah, Africa is Arjun.

If you.

Dr, please start by introducing your professional journey in academia.

I'm not sure I caught that — I'd like to start by hearing a little about your academic path so far. Could you walk me through your journey in academia?

OK, I start my. I start my journey as an entrepreneur. I I built a company from. From scratch. Our company was serving. Our testing services and building learning management system. From there I slowly moved on to.

I'll become a test engineer. And from there I slowly moved on to become. Senior lecturer and I worked in Tanzania. And from Tanzania I work.

Right, so as you've moved into academia, what's one foundational concept or method you most enjoy teaching to students?

Okay, that's a solid transition from industry into academia. When you became a senior lecturer, what was your approach to introducing new material in your classes—did you rely more on hands-on labs, lectures, or something else?

Start to my current role.

That's quite a varied path, touching both industry and academia across different countries. When you transitioned into teaching roles, was there a particular foundational topic or concept—maybe in multimedia, AI, or a related area—that you found especially rewarding to introduce to students for the first time?

Ah, yes, of course. Uh, the recently. Even I built a course. Called as prompt to prototype. Which is. Helping students to build. Right from scratch. Without much of coding knowledge. And this was. Purely. From the experience I can gain from the industries. And I found. The gap that students had in the academia. Add this course.

That's an interesting point. Could you elaborate a bit more on that?

Once a product is ready, then we will share it. Across social medias of Base 44 and Vitap University and Showcase. How real-world products were built. From prompt.

Arjun. Are you here with me?

Given your work developing courses like "Prompt to Prototype" and your background bridging industry and academia, where do you see the most promising, fundable research directions emerging for you over the next few years? What kinds of grants or external funding would you aim for to support that work?

Yes, I'm here. You mentioned showcasing the students' MVPs on social media and university platforms—what's your strategy for turning that kind of exposure into concrete research outcomes or external funding opportunities for your group?

Oh, thank you, Thank you.

Arjun, there is a small delay between.

You've described how students went from initial problem statements to MVPs and showcased their work—I'm curious, beyond social media exposure, how do you leverage those student-built prototypes or research products to attract external funding or industry partnerships for the university?

Right, there's sometimes a lag—thanks for your patience. Dr, given your experience collaborating with Base 44 and running industry-partnered courses, what steps would you take to turn those partnerships into externally funded research projects or consultancy engagements that benefit both your students and the university?

Of climatic conditions. Where each of. Each user will plant a tree. And they will digital 12 in application and they will see and monitor the. Pre grown and also for each of the tree that is. Planted How much of CO2 absorption is done? So carbon footprints reduction. Is one of the main goals of that particular project. Likewise, we have many societal. Projects which we are building via this MVP. The other idea we have is. When student get a first hand. View on how to build societal projects and help the help to solve real world problems. And. The major problem that. They had previously was when they tried to build a. End to end complete product. They lack certain technical requirements or some. A technological. Gaps. For example, they don't know how to integrate it with a cloud system or they know how to add user interface. But now with. The prompt. To prototype and all of them can be built. Using. Clearly using the.

Prompt students really enjoy building these. Product.

Right, so you’re using MVPs focused on societal impact to give students hands-on experience while also bridging technical gaps through industry tools. When it comes to scaling these projects up—say, turning one into a funded research initiative—what’s your process for identifying the right external funding sources or industry partners, and how do you pitch the value of your work to them?

An example or. As a portfolio we'll be able to vouch for. For consultancy projects.

Okay, let's shift gears to your teaching practice. You mentioned running the "Prompt to Prototype" course with students who had limited coding backgrounds—imagine you had to teach that same course to a much larger group, say 200 students, but you couldn't use slides or traditional lectures. How would you structure the sessions to keep everyone actively engaged and learning?

Professor, let's talk a bit about the broader responsibilities of being a faculty member. Accreditation cycles can be demanding—if you joined our department and found that outcome assessment data was inconsistent across courses, how would you approach fixing that?

In in the recent assignment also. We are working on some of these things. For example, I'm specifically working on. Uh uh, utility tool. That will help us to do poco mappings and try to help us. To have. A complete. Uh system where we will be able to upgrade the syllabus. So how? And what we will try to do is we will try to see. The obese.

Okay, so you’re working on a tool to help map program outcomes and keep the syllabus in sync. Day to day, what’s one thing you’ve found most challenging or time-consuming in making sure accreditation data actually lines up with what’s happening in the classroom?

Committees.

Imagine this situation, Professor: a student comes to you with a formal complaint, alleging your grading was biased. At the same time, your department head is pressuring you to raise pass rates for the course. How would you handle this tension between maintaining academic integrity and responding to institutional expectations?

We definitely have. So the first thing I always have in class is. A complete and open transparent evaluation system. As soon as. The first day in class. The first day in class. We show them. The entire syllabus. We show rubrics. And evaluation style and model for each of the components that are available. And what will be the fall back? What will be the criterias when a revaluation can be attempted? So all of these instructions are given in frequent intervals. The first day I give them the entire instruction and before every exam or every. Assessment cycle. I give them the instruction and post assessment cycle before an evaluation. Starts for example if. A Cat 2 exam is complete. When the S uh. Evaluation of the paper Stats I. Show them the question vapor. What should be answered? What will be the rubrics? And what will be the mugs? Apart from that, I also came with an open system. Where I also have. The rubric scale. Where the student will be able to. Click on the rubrics and actually find out by himself what will be his. Mark that he would. Be able to obtain when he. Accomplish the points. Which are the points which has to be present in the? Answer key.

Wow, this is again a real tough question. We make sure that. We always achieve the bell curve and out of the experience.

You mentioned aiming for the bell curve—can you walk me through exactly how you'd respond if, after your review, the department head still insisted you adjust grades in a way you felt was academically inappropriate?

As a teacher. We be the leader in the class. And we make sure that there is no interference from. The other faculties are.

That's a pretty robust system for transparency. And if your department head still insisted you adjust grades in a way you felt compromised academic standards, what would you do?

The other. Heads for mark improvements. Uh, when everything is kept completely transparent. It becomes very satisfactory for the students as well as. The heads. As well As for ourselves, keeping transparent is the key point, and keeping all of them documented and. Well-informed the students when kept well informed on the way, how it will be evaluated, what will be the rubrics and what will be. The key points for example. For every assessment. I tend to give them. An evaluation.

Switching gears a bit—given your hands-on work with Base 44 and focus on building real AI products, do you have industry connections that could help translate those experiences into internships or placement opportunities for your students?

So that this particular problem gets solved.

You’ve clearly put a lot of thought into transparent grading and student communication. Let’s shift focus—when you’re designing a multimedia or AI-driven course, how do you decide which emerging technologies or tools to include in the curriculum, given how fast the field changes?

Yeah, this one is also quite practical, and every week I also face the same challenge. This week we start with a new. Before the weekends we have another new AI tool coming. Now what happens is it is not about the frequency of the change, it is. The demand of the industry, what has to be incorporated and also a baselining should be done. When we keep on. In this particular current scenario, if we keep on. Changing it is it is not possible to adapt. The syllabus. Or to adapt. To the growing changes that is happening. Frequently every week. If there is change, it is not possible to. Upgrade our syllabus every week. So what we will try to do is we'll try to find out. What is the?

Right, it sounds like you prioritize industry relevance and try to filter what actually has lasting impact versus just chasing every new tool. When you're picking technologies for your curriculum, do you consult with industry partners, alumni feedback, or is it mostly your own research and observation?

To identify what will be the futuristic trend based on that, slowly we will try to incorporate. Generic changes that will help. The students. To adapt to any changes that may happen. So the generic knowledge of, for example, assume that we want to. Learn how AI can be used. As a developer to develop code fast. Or how AI can be used to test. The codes faster. So we need not have to worry about what type of. Tool or which version or which company is going to present the tool. It is enough if the student understand how an AI can be used. To to. Scale the codes faster or to test a software faster.

The adaption to the. Tool that will be available. During his time in the industry will become very easy. So it is on generic learning and forecasting and finding out what will be the industries demand.

Makes sense—you’re focusing on core concepts and adaptability, not just tool-chasing. Thinking about student evaluation, what's your approach for designing exams or practical assessments that fairly measure both the theoretical understanding and hands-on skills in a multimedia or AI course?

Seeing the change that is happening rapidly. We might not be able to interrupt everything in the syllabus. But. The generic incorporation should keep on happening. By industry connects. Guest lectures and alumni connect. And with a lot of connections that I had.

Right, so you’re aiming for students to learn underlying principles so they’re adaptable no matter which tool comes up. Shifting gears—when you’re tasked with evaluating student projects in these AI or multimedia courses, how do you ensure consistency and fairness across different evaluators, especially if multiple faculty are involved?

Previously worked in the industry. Uh, for every course. I tried to Bing at least two guest lectures through which. They will share their experience about. What is happening in the industry? What is the future trend? One of the examples that. Uh, recently like 2-3 days back. Oracle. Has to. Layoff around like 30,000 engineers this. I've been discussing with my students. For more than. Uh, 2-3 months. How? How is this even possible? This is this was possible because. Of the tight. A networking that we have across our alumni's. Our.

Right, it sounds like you use industry connections and alumni to keep your courses relevant without getting lost in the pace of change. Shifting to exam duties—when you’re evaluating a practical lab or project in a media or AI course, how do you ensure your assessment is fair and consistent across a large group of students?

Friends who are networked and working in the industries. So frequent of. Frequent communication and discussion on this helps us to understand what actually is happening in the industry. What trend is coming up? And how? And how and what are all the skills that are required for our students? To be equipped. To shine in the arc. Area.

Alright, you've talked a lot about keeping students updated and connected with industry, which sounds valuable. Shifting to your role in student evaluation—when you're assigned as an examiner for a course you didn't teach, how do you ensure your assessment is fair and aligns with the original instructor's standards?

You've got a strong focus on industry alignment and leveraging your network—sounds like you keep students really plugged into what actually matters. Let's talk specifically about student evaluation and exam duties: when you're designing or grading a practical exam in a multimedia or AI course, what's your approach to ensuring fairness and consistency across different examiners or batches?

Oh yes. Now for example. A course might not only be handled by 1 faculty. We will have multiple slots and we will have multiple faculties handling this. So what we will have is we will have some. One who was called as a course coordinator. And in. During the start of the course itself, we will decide. What has to What has the syllabus to become? Uh, completed. In what depth and what are the experiment that has to be executed in the lab? Day wise, assume that we have 12 laps. For each of the lab, what are the experiment to be executed? How will they be evaluated? What is the last day to upload in the? AB top once this is done right uh. Before we have the exam, for example, we will have one big. For lab fat. During Before we start the lab fit, we will try to prepare some 5 to 15 different sets of question papers, which will be.

Randomly or. Alternatively. This period for the students during the exam. And how we will maintain the consistencies. All the faculties will sit down together. And we'll discuss what was accomplished in that particular. Lab sessions, for example, what was the 10 experiment that was completed? What were the 10 scenario that. Or the 10 concept that was discussed. Based on that we will come out with various sets of question papers and this all sets of question paper will have the same complexity but the questions will be different. Based on that, we will be able to do a fair evaluation across different slots. For a same course, for example, assume there's a software testing lab. There are going to be 3 slots. And each slot handled by. Three different faculties. And. There will be around 60 to 65 students across these slots for this, what we'll do and we have around. A 12 lab experiment which was done for software testing. So what we will do, we will try. And discuss with all the three faculties, all the three slot faculties. And we will come out with. Five sets of question paper for each of the. Lab slots.

Right, so you’ve got a course coordinator setting standards and mapping out labs and assessment deadlines. When it comes to those 5 to 15 different question paper sets for the lab exam—how do you ensure that all the questions are balanced in difficulty and actually test the same core competencies, so that no student gets an unfair advantage?

Right, so you make the question sets together for consistency. Let’s say, after results are out, a group of students from one batch all complain their set was harder than another batch’s—how do you handle that kind of challenge to fairness in practice?

But this will ensure.

Alright, we're wrapping up. Is there anything you'd like to ask about the role or the team?

Yes.

How was my interview with?

Of course, Dr. What's your question?

Of course, Dr. If you’re asking for feedback on the interview itself, I can share that now’s not the time for detailed performance feedback, but I genuinely appreciated hearing about your transparent grading practices and how you connect students with industry trends. Was there anything else you wanted to ask about the position or the institution?

Can can you share a little about the position?

Certainly. The position involves teaching and mentoring students in emerging technology areas, running both classroom and lab sessions, evaluating student work, and guiding student projects and research. You’d also be expected to contribute to publications and support departmental academic activities. Is there anything more specific you’d like to know about the role?

Ha, looks like.