Two Sigma Challenge

Dive into the future of higher education with SMARTA (Student Motivation and Reflective Training AI-Assistants). This project introduces AI chatbots as personal study coaches, aiming to bridge the educational gap known as the Two Sigma Problem. With the power of AI, SMARTA offers a trio of specialized chatbots designed to enhance student motivation, deepen engagement, and personalize the learning journey for over 5000 students at a German university. From fostering empathetic support to encouraging self-directed learning and interactive dialogues, these chatbots mark a significant leap towards mimicking the personalized touch of one-on-one tutoring. Discover how SMARTA leverages AI to turn the Two Sigma challenge into an unparalleled opportunity for students alike. Get ready to explore the cutting-edge intersection of technology and education, where personalization meets excellence. Join us on this enlightening journey to redefine the landscape of higher education through the lens of AI.

AI Teaching Master, Process Expert, or Excellent Avant-garde?

Where does your university stand in the field of AI? The AI Maturity Matrix can assist with self-assessment.

Do most professors see AI more as a danger than an opportunity? Does the examination office ban the use of GPT? This suggests a traditional and careful approach.

Or has your university already included AI as an optional module in every degree program, training teachers to integrate it into their subjects in a practical way? Are the people in charge of accreditation informed about including AI in new module handbooks? If so, your university might be on its way to becoming an AI teaching leader.

Does your administration, marketing, and admissions team, as well as your research department, make extensive use of AI? Do you give teachers the chance to use generative AI to create case studies or tasks? Do students also have access to GPT in a way that protects their privacy? If yes, then you’re likely on the path to becoming an AI process expert.

Or are you working on AI innovations both in your curriculum and in the processes of administration and learning? Congratulations. You’re on your way to being a part of the excellent AI-Avant-garde!

To answer the question, “Where does the university stand in the field of AI?”, we are currently developing a classification model including a questionnaire. This tool aims to enable a university to conduct a self-assessment.

To compare this with an external evaluation, clear definitions and measurement criteria must be developed for each axis and category. Integrating a third dimension will also help to capture the qualitative aspects of AI integration. For example, traffic light colors can be used to indicate whether the integration is successful and comprehensive.

Reading example: The university depicted in Quadrant 9 has integrated AI into its curriculum MODERATELY, meaning only in specific modules. However, these specific modules are rated as rather poor quality (red), for example, because the modules are not current or not relevant to practice. The university has HIGHLY integrated AI into its processes, meaning in both administration and teaching, and this has been achieved with satisfactory quality (yellow) so far.

As part of this project, a national AI index of universities in Germany is being created, spanning across various institutions. The goal is to also provide interested universities with a guide on how to progress from one stage to another, for example, from being an “AI Teaching Experimentator” to an “AI Teaching Master”. Initial ideas are promising.

The quick test can be found here:

MUSE (Motivation-Understanding-Schema for Effectiveness)

The chatbot ALIX’s job is to encourage students. As part of the SMARTA project, we’re looking to see if students come to the chat feeling motivated or not. We’re also trying to find out if chatting with ALIX changes their motivation levels. For example, a student might start the chat in a bad mood and not feel better after talking to ALIX. We call this a ‘Stagnation Spiral.’ Ideally, we want ALIX to help students who are feeling down become more motivated, which we call a ‘Motivation Reboot.’

Currently, we can measure the mood/sentiment of each chat and how it changes (!). We don’t know the users’ names, but we can analyze and record the chat’s sentiment. This lets us track how often something like a ‘Euphoria Decline’ occurs. Right now, the percentages in our matrix are just rough estimates. We’ll publish exact numbers in spring 2024.

Machine AI vs. Human Algorithms

In 1956, at the first AI conference, there was a consensus that machines could simulate intelligence. The debate was whether this would be best achieved through machine learning algorithms or human-written code. Today, many believe that AI will revolutionize university software. However, some argue that human algorithms, which have been effective and legally compliant for years, are still essential.

We believe that human algorithms are crucial for legally significant decisions, such as calculating final grades on a diploma supplement or determining a faculty’s budget. Algorithmic Intelligence, which is code written by humans, remains vital for universities. Human algorithms follow specific rules, are precise, and lack creativity. They don’t alter themselves. When a decision is made by an algorithm, it’s possible to trace back the reasoning, ensuring legal compliance. Plus, you don’t need tons of examples to train a human algorithm.

Consider a new university using generative AI to assign final grades. They would need many examples to train the model. Then, they might end up giving different grades to similar students on different days without understanding why. That would be disastrous.

Therefore, SMARTA focuses on using AI not for decision-making tasks but for areas where creativity is key, especially in generating text. We use various language models like GPT. Instead of the standard interface, we strictly utilize the API. This approach allows us to seamlessly integrate AI into existing systems like a Campus Management System and control both input and output.

GMW conference: Together with Man and Machine in Research and Education.

The upcoming annual conference of the Society for Media in Science will feature our SMARTA, the”Student Motivation and Reflective Training AI-Assistants.” SMARTA seems perfectly aligned with this year’s theme of the GMW conference: “Together with Man and Machine in Research and Education.”

Heres a german video adressing students to join the event:

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An interview with Ada Lovelace

October 9th is Ada Lovelace Day. Why is this important to us?

In collaboration with universities from Germany, Greece, Bulgaria, Italy, and North Macedonia, we participate in the project “ADA”. ADA aims to support female entrepreneurs. As part of this effort, we developed a chatbot named SOFIA. Additionally, the interview below is a small project that was used for social media purposes.