Conversational learning: How chatbots open up new approaches to training
How chatbots can improve learning whilst reducing workload
For years, mobile learning and micro-learning have been gaining importance within the field of digital further training. Employees are also taking more responsibility for their own learning, informal learning is becoming more important and there is a demand for a low-threshold access to digital learning. In that regard, messaging services are seen as a learning medium with future potential, which has only been minimally developed so far. The situation is similar for digital assistants and chatbots, also known as ‘conversational interfaces’. Exciting new application areas are opening up due to low access limitations, comfortable navigation via direct dialogue and optional content access in the ‘moment of need’.
Chatbots in corporate training
Bots take on a variety of tasks. They book and register, remind participants and trainers of appointments or tasks and provide information about qualification offers, dates and events, pricing, trainers and training locations. They help answer important questions and solve organisational issues or problems in regards to the implementation of the learned material quickly and easily. As personal points of contact and assistants, they reduce the training organisation workload of personnel developers and training managers, while taking care of routine tasks for trainers. As such, they support those organising the learning activity as well as the learners themselves.
Bots as tutors: Conversational learning
But chatbots can do more than take care of tasks and answer standard questions. After all, when we interact with a chatbot to learn something and pursue our further training, this creates a dialogical learning process: Conversational learning. The organisation of further training can therefore access a host of new and extensive options to support individuals through the learning process, guide employees and continue to push the boundaries of classroom-based learning.
For example, learnbots answer frequently asked questions patiently and around the clock in their function as virtual supporters and tutors. They provide concrete expert knowledge; take on the role of coach and instructor in question-and-answer dialogues or in drill-and-practice exercises to check what has been learned. They are partners and learning buddies, there to help further explore, practice and absorb what has been learned together. Options for training applications, in the narrower sense, are particularly exciting. A digital vocabulary trainer, a talking ‘lexicon’, a tutorial system that knows all about the new products, or even dialogue based interactive fiction, which uses a playful approach to take the user into their own world of learning. This is conversational learning at its best – learning via dialogue with a quasi-human counterpart.
Tips for your concept and implementation
Digital assistants have to be adequate interlocutors in order to gain acceptance and generate real learning progress via conversational learning. Towards that end, the system in question has to be developed to fit the actual learning context and with a specific goal in mind as well as being expanded continuously. A clear idea of the specific application, goals and the target audience is an important prerequisite for this. Many developers and authors equip their bots with their own persona to appear as ‘human’ as possible when talking to users whilst being unique at the same time. It is a true form of art to develop good dialogues with factually correct content and a conversation technique that involves the human dialogue partner.
The path to your own bot
Just like any successful project, developing a learnbot starts with a briefing. During the briefing phase, we clarify requirements and utility, agree on goals, identify the target audience and define our requirements and parameters like time, quality and budget. During the concept phase, we define the bot persona with a view to use case and target audience, and design the dialogue concept. On that basis the treatment and script are subsequently developed. Next, a pilot operation provides additional insights about actual usage and requirements. In the live operation that follows, we recommend continued monitoring of the bot and regular evaluations of conversation logs to ensure continuous improvement. Imagine the bot as a company employee; you first teach them what they have to know in order to reliably accomplish their core task. Over time, they face questions, which they cannot answer initially. But through further training they get better and better at their job until one day they become the first point of contact in their field of expertise.
Chatbots offer many practical applications for further training, not just in terms of organisation and service but also for learning as such. Conversational learning opens up varied forms of learning allowing us to meet the current requirements of corporate learning in terms of flexibility, accessibility and value added for the user. Success is not merely a question of having the right technology but above all having a good concept.
Learn more about conversational learning applications and talk to learnbot Kim about artificial intelligence at jix.ai/en/