Personalized Self-Assessment Tool Using a Telegram Bot: A Case Study on Data Structures and Algorithms

Personalization of self-assessment educational tools plays a key role in enhancing the learning process. By allowing students to tailor the content and pace of their learning according to their individual needs, these tools encourage a more learner-centered approach. Our proposal consists in definin...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE Global Engineering Education Conference s. 1 - 8
Hlavní autoři: Lopez-Ostenero, Fernando, Martinez-Romo, Juan, Plaza, Laura, Araujo, Lourdes
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 08.05.2024
Témata:
Chatbots
Computer science
Data structures
Engineering education
History
Navigation
personalization of teaching
Proposals
self-assessment tool
telegram bot
ISSN:2165-9567
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Personalization of self-assessment educational tools plays a key role in enhancing the learning process. By allowing students to tailor the content and pace of their learning according to their individual needs, these tools encourage a more learner-centered approach. Our proposal consists in defining different personalization mechanisms for a self-assessment tool. This tool allows students to navigate the hierarchy of concepts of the subject and suggests them exercises covering the different concepts. After the student selects one of the possible answers, the tool informs if the student is right or wrong, The study has been carried out in a Computer Science course devoted to the teaching of algorithms and advanced data structures. However, the proposed tool and mechanisms can be easily exported to other subjects and topics. The tool has been implemented as a Telegram bot, which facilitates access to the tool from different platforms. The personalization mechanisms introduced in the tool on the one hand, allow to present the questions on each topic in increasing order of difficulty. This is achieved by analyzing the results of the exams in which the questions were originally proposed. In addition, the tool records the user's history, avoiding repeating questions already answered correctly and providing data on the user's performance. According to a questionnaire answered by the students, the tool, and in particular the personalization mechanisms, has been very useful for them in the preparation of the subject.
ISSN:2165-9567
DOI:10.1109/EDUCON60312.2024.10578697