Related Experiment Video
Updated: Mar 12, 2026
06:37
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
5.6K
SSC-BanglaTutor: A curriculum-aligned Bengali dataset for intelligent tutoring systems.
Eshraque Jabid Ifti1, Fihab Ifty1, Mehadi Hasan1
1Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka 1229, Bangladesh.
Data in Brief
|March 11, 2026
Summary
A new Bengali dataset with 11,286 hint-based science questions aids AI tutoring for Bangladesh's Secondary School Certificate (SSC) curriculum. This resource supports personalized learning and low-resource Natural Language Processing (NLP) applications.
Area of Science:
- Educational Technology
- Natural Language Processing (NLP)
- Artificial Intelligence (AI) in Education
Background:
- Developing AI-powered tutoring systems requires specialized datasets for effective fine-tuning.
- Existing resources often lack linguistic diversity and curriculum specificity for regional educational needs.
- Bangladesh's Secondary School Certificate (SSC) science curriculum presents a unique educational context.
Purpose of the Study:
- To introduce a novel Bengali-language dataset for AI-powered hint-based tutoring systems.
- To support the fine-tuning of large language models (LLMs) for educational applications in Bangladesh.
- To enhance personalized feedback and learner modeling in intelligent tutoring systems.
Main Methods:
- Creation of 11,286 hint-based question-answer entries manually from government textbooks and exam materials.
- Inclusion of Biology, Chemistry, and Physics questions aligned with the SSC curriculum.
- Development of candidate answers with one correct and several plausible incorrect options, alongside a convergence score.
Main Results:
- The dataset comprises 4859 Biology, 3034 Chemistry, and 3393 Physics questions.
- Each entry includes a convergence score to gauge hint effectiveness and student progress.
- UTF-8 encoding with select English terms ensures accessibility and NLP application value.
Conclusions:
- The dataset provides a robust foundation for developing linguistically inclusive and educationally effective intelligent tutoring systems.
- It facilitates personalized learning experiences and offers insights into student learning trajectories.
- The resource is valuable for both native learners and low-resource NLP research.
Related Concept Videos
01:31Student t Distribution
14.6K
The population standard deviation is rarely known in many day-to-day examples of statistics. When the sample sizes are large, it is easy to estimate the population standard deviation using a confidence interval, which provides results close enough to the original value. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
The Student t distribution was developed by William S. Goset (1876–1937) of the...
The Student t distribution was developed by William S. Goset (1876–1937) of the...
14.6K
01:18Introduction to Learning
1.3K
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
1.3K
01:26Classification of Systems-I
648
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
648
01:31Classification of Systems-II
544
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
544
01:22Purposive Learning
558
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
558
01:21Cognitive Learning
1.5K
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
1.5K