Artificial Intelligence Helps a US Online Education Company to Communicate Better with Students

A major education management organization that provides online curriculum to homeschooled children and other schools in the US. The adaptive literacy program is aimed at helping kindergarten to twelfth grade students on improving foundational skills, literature, language and learn through games and short lessons. Under this program, teachers and administra-tors receive student progress reports as well as the opportunity to be in constant contact with students through online chats.

Supporting online chats can be a daunting task, even more if you are a dedicated teacher that just happens to use that medium in order to communicate with and help students. As the reader might guess, students sometimes do not state clearly what they do not understand, and some of them engage in off-topic conver-sations. These issues take up a significant fraction of the teacher’s time and efforts, time that could be focused in other tasks related to teaching and improving lessons. The company realized its need to boost the productivity of their online teachers and recognized that an artificial intelligence-powered assistant would help them to process conversations faster. Furthermore, artificial intelli-gence could assist the students with the initial steps of working towards an answer without giving it away, deal with problematic cases, and reroute conversations when necessary.

The objective, then, was to create an AI assistant able to guide students through their learning process in a human-like way. This assistant had to be tailor-made to fit the client’s e-learning environment and to comply with teacher behavior guidelines and educational regulations.

THE CHALLENGE

Globant’s solution was able to scale and differentiate something as unique as a teacher guiding a student to find answers to different problems. The performance of an AI solution depends on several factors: data availability is fundamental, but another key factor is the ability of the team at Globant to transform the outputs of the AI algorithm into appropriate user experiences.

Working in close collaboration with the client, the team imple-mented a custom-built recurrent neural network architecture - the state-of-the-art solution for language processing- able to learn from historical data on millions of actual interactions between students and teachers. Built with PyTorch, a Deep Learning framework for fast, flexible experimentation, the neural network was trained using specialized high-performance hardware. A cloud-based deployment then enables scalability by launching new trained chatbot instances as required by user demand.

THE SOLUTION

Not all AI solutions may be optimal for a given problem, so the team always approaches projects with an experimental mindset. Artificial Intelligence (AI) value creation should be guided by rigorous validation of ideas and thorough testing of key hypotheses, followed by iterative cycles of improvement. Therefore, Globant’s team performed an initial 12-week Proof Of Concept (POC) in which a standalone bot “brain” was developed and then deployed as a Slack app, demonstrating its feasibility. The POC included assessment of data capabilities and of required state-of-the-art technology. A team consisting of data scientists, data architects and cloud computing specialists was specifically assembled to create and deploy the brain of the chatbot, its data infrastructure and the integration with existing platforms.

After the success of the initial POC, a production-ready version fully inte-grated with the client’s platform was developed in approximately seven months time. This first production version was deployed in December 2017. Currently, the team is actively working on improvements based on user feedback, with an improved version coming out approxi-mately every two months.

Additionally, a data platform was created to support the associated pro-cesses of chatbot training, performance feedback loops, and reporting. This cloud-based big data platform stores transcripts of all ongoing con-versations in the client’s application, either between humans or involving the chatbot. This data grows at a rate of over 1 million lines per month and constitutes an ever-expanding corpus from which our AI learns.

This project was a great experience for both Globant and our client. We showed them how to successfully build a custom AI solution tailored to the client’s needs. Our experimental and data-centric approach also yields valuable insights along the way which enrich and enhance the final product. In six months of operation, the bot showed its ability to accurately deal with situations such as off-topic behavior, thus easing the teachers’ workload. In other cases where the performance deviated from the expected outcome we set up a feedback loop with human reviewers to enable retuning and retraining of the neural network. In addition, Globant’s team created a framework and approach to enable the development of Deep Learning projects for future uses within the educational services provider business group.

We have faced many challenges along the way, as we worked to make our solution ever more capable. How do you make end users embrace and not resist an AI solution? How do you incorporate quality control to an “intelligent” product? Our timely responses to all such challenges are demonstrating Globant’s capability as a key player in the coming AI revolution.