Modeling a Student–Classroom Interaction in a Tutorial-Like System Using Learning Automata

Abstract

Almost all of the learning paradigms used in machine learning, learning automata (LA), and learning theory, in general, use the philosophy of a Student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways, including the scenario when there are multiple teachers or a hierarchy of mechanisms that collectively achieve the learning. In this paper, we consider a departure from this paradigm by allowing the Student to be a member of a classroom of Students, where, for the most part, we permit each member of the classroom not only to learn from the teacher(s) but also to "extract" information from any of his fellow Students. This paper deals with issues concerning the modeling, decision-making process, and testing of such a scenario within the LA context. The main result that we show is that a weak learner can actually benefit from this capability of utilizing the information that he gets from a superior colleague-if this information transfer is done appropriately. As far as we know, the whole concept of Students learning from both a teacher and from a classroom of Students is novel and unreported in the literature. The proposed Student-classroom interaction has been tested for numerous strategies and for different environments, including the established benchmarks, and the results show that Students can improve their learning by interacting with each other. For example, for some interaction strategies, a weak Student can improve his learning by up to 73% when interacting with a classroom of Students, which includes Students of various capabilities. In these interactions, the Student does not have a priori knowledge of the identity or characteristics of the Students who offer their assistance.

Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow

“…BDTF approach could be extended to the tutorial-like systems similar to the LA applications for a generalized concept of ITS proposed by Hashem ( 2007 ). Since we are using LA, we can integrate the idea of having an stochastic teacher (Hashem and Oommen 2007 ), modeling a classroom of students where artificial students can interact and learn from each other as well as the teacher (see Oommen and Hashem 2009a , for such a model), and propose an adaptive learning model of teacher and how teaching abilities of a teacher can be improved during the process (inspired by Oommen and Hashem ( 2013 )).…”

“…Clement et al (2015) propose an LA for seven to eight years old school-children learning to decompose numbers while manipulating money. Even though a generic solution is presented by Clement et al (2015) relying on multi-armed bandit, there is no evidence that a similar approach is viable for use for adults and contexts addressed in online learning (see also Hashem and Oommen 2007;Hashem 2007;Oommen and Hashem 2009a, b, 2010, for LA based models for a generalized framework of tutoring system, called tutoring-like systems).…”

“…In a tutorial-like system, the teacher also might be stochastic and learns through the process of training (Hashem 2007 ). The design and analysis of a tutorial-like system model could involve modeling of a student (Oommen and Hashem 2009b ), modeling of a classroom of students where artificial students can interact and learn from each other as well as the teacher (Oommen and Hashem 2009a ), modeling of a (stochastic) teacher (Hashem and Oommen 2007 ), modeling the domain knowledge (Oommen and Hashem 2010 ), and modeling how teaching abilities of a teacher can be improved (Oommen and Hashem 2013 ).…”

Modeling a Teacher in a Tutorial-like System Using Learning Automata

“…The students themselves work collectively in a Classroom, as explained in [14], the details of which are omitted here.…”

Fast and Epsilon-Optimal Discretized Pursuit Learning Automata

“…the adaption to the environment. LAs have found a broad range of applications reported in the literature, such as game playing [2]- [4], pattern recognition [5], classification [6], knapsack problem [7], tutorial-like system [8], [9], object partitioning [10]- [13], cellular automata [14], telephony routing [15], [16], scheduling [17], minimum-spanning circle problem [18], congestion avoidance [19], function optimization [20], [21], resource allocation and assignment problems [22]- [24], automaton controller [25], control absorption columns, flexible manufacturing plants, and other applications such as dryers, vehicles, irrigation canals, multimedia network, robots, liquid-liquid extraction columns, bioreactors, distributed fuzzy logic processors, image processing, and data compression. Various LAs, their properties and applications have been reviewed in survey papers [26], [27] and books [28]- [32].…”