Search results for "Tutoring"

Improving Assessment of Students through Semantic Space Construction

2009

Assessment is one of the hardest tasks an Intelligent Tutoring System has to perform. It involves different and sometimes uncorrelated sub-tasks: building a student model to define her needs, defining tools and procedures to perform tests, understanding students' replies to system prompts, defining suitable procedures to evaluate the correctness of students' replies, and strategies to improve students' abilities after the assessment session.In this work we  present an improvement of our system, TutorJ, with particular attention to the assessment phase. Many tutoring systems offer only a limited set of assessment options like multiple-choice questions,fill-in-the-blanks tests or other types …

A combined semantic-syntactic sentence analysis for students assessment

2010

TutorJ is an Intelligent Tutoring System able to fulfill the requests of a student with a learning path inside didactical materials. To this aim, it must assess the level of training of the learner. In the first version of TutorJ this goal was reached through a conversational agent whose linguistic interaction enriched by a LSA-based text analysis. This approach suffers from the limitations of LSA as a bag-of- words approach. Next, morphosyntactic comparison of sentences' structures was implemented. In this paper we present a new version of the assessment procedure involving both semantic, and morphosyntactic analysis user's sentences.

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

2020

An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner and difficulty of the tasks such that the learner experiences a state of flow during the learning. Flow is a mental state that psychologists refer to when someone is completely immersed in an activity. Flow state is a multidisciplinary field of research and has been studied not only in psychology, but also neuroscience, education, sport, and games. The idea behind this paper is to try to achieve a flow state in a similar way as Elo’s chess skill rating (Glickman in Am Ches…

Teaching self-regulation strategies via an intelligent tutoring system (TuinLECweb): Effects for low-skilled comprehenders

2018

Anche quella foto acquistò colore

2019

È una raccolta di considerazioni pedagogiche radicate in episodi reali ambientati nella Palermo degli anni 90; è l’esempio di come può nascere l’interesse per la ricerca scientifica in ambito pedagogico in seguito ad alcune esperienze di tutoring universitario svolto in modo riflessivo. Un testo che può aiutare molto gli studenti, specialmente nei loro primi mesi di impatto iniziale con la realtà accademica. L’approccio è accattivante, incuriosisce, attira l’attenzione del giovane ventenne perché comunica idee positive sullo studio e sulle relazioni interpersonali mediante brevi, ma frequenti, riflessioni sullo studio universitario.

Evaluation and Accreditation System of External Internship Tutors - SEATPE

2020

La Universidad de Valencia ha implementado desde 2012 un Sistema de Evaluación y Acreditación de Tutores de Pasantías Externas (SEATPE) a través de su Fundación Universidad-Empresa, ADEIT, bajo la dirección del Vicerrector de Empleo y Programas Formativos. Los objetivos principales de este sistema son mejorar la calidad de la tutoría de pasantías externas implementando mecanismos para reconocer el buen trabajo de los tutores y aumentar el compromiso de las empresas y entidades con la capacitación práctica de nuestros estudiantes. Está dirigido a los dos perfiles de tutores: académicos y empresas. Los tutores que acceden al SEATPE obtienen una "Mención de calidad" en el caso del tutor académ…

Domain Specific Knowledge Representation for an Intelligent Tutoring System to Teach Algebraic Reasoning

2012

Translation of word problems into symbolic notation is one of the most challenging steps in learning the algebraic method. This paper describes a domain-specific knowledge representation mechanism to support Intelligent Tutoring Systems (ITS) which focus on this stage of the problem solving process. The description language proposed is based on the concept of a hypergraph and makes it possible to simultaneously a) represent all potential algebraic solutions to a given word problem; b) keep track of the student's actions; c) provide automatic remediation; and d) unequivocally determine the current state of the resolution process. An experimental evaluation with students at a public school su…

Gui-driven intelligent tutoring system with affective support to help learning the algebraic method

2017

Despite many research efforts focused on the development of algebraic reasoning and the resolution of story problems, several investigations have reported that relatively advanced students experience serious difficulties in symbolizing certain meaningful relations by using algebraic equations. In this paper, we describe and justify the Graphical User Interface of an Intelligent Tutoring System that allows learning and practising the procedural aspects involved in translating the information contained in a story problem into a symbolic representation. The application design has been driven by cognitive findings from several previous investigations. First, the process of translating a word pr…

Emulating Human Supervision in an Intelligent Tutoring System for Arithmetical Problem Solving

2014

This paper presents an intelligent tutoring system (ITS) for the learning of arithmetical problem solving. This is based on an analysis of a) the cognitive processes that take place during problem solving; and b) the usual tasks performed by a human when supervising a student in a one-to-one tutoring situation. The ITS is able to identify the solving strategy that the student is following and offer adaptive feedback that takes into account both the problem's constraints and the decisions previously made by the user. An observational study shows the ITS's accuracy at emulating expert human supervision, and a randomized experiment reveals that the ITS significantly improves students' learning…

Using System Dynamics to Model Student Performance in an Intelligent Tutoring System

2017

One basic adaptation function of an Intelligent Tutoring System (ITS) consists of selecting the most appropriate next task to be offered to the learner. This decision can be based on estimates, such as the expected performance of the student, or the probability that the student successfully solves each particular task. However, the computation of these values is intrinsically difficult, as they may depend on other complex latent variables that also need to be estimated from observable quantities, e.g. the current student's ability. In this work, we have used system dynamics to model learning and predict the student's performance in a given exercise, in an existing ITS that was developed to …