OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described

The effectiveness of using intelligent tutoring systems to increase student achievement

Intelligent Tutoring Systems could be used to provide differentiated instruction. This review examines qualities of Intelligent Tutoring Systems and their impact on student achievement. Thirty peer-reviewed research studies published from 1997 to 2019 were selected for analysis. This review considers how intelligent tutoring systems compare with other methods of instruction, and how an intelligent tutoring system’s on-screen tutor impacts student achievement. Finally, this review considers methods of ITS personalization and how those methods impact student achievement. The reviewed research studies indicated that ITS was more effective than all forms of instruction except small group and individualized instruction. Additionally, on-screen agents in and personalization of Intelligent Tutoring Systems often have a positive impact on student learning. Recommendations for classroom implementation of intelligent tutoring systems and suggestions for future research are discusse

Un sistema de tutoría inteligente para la mejora de la competencia escrita del alumnado de primaria

P. 251-260Diferentes revisiones empíricas y meta-análisis en el ámbito de la instrucción en escritura han señalado la instrucción en estrategias y el uso de programas informáticos como apoyo instruccional en las tareas de composición escrita como dos formas efectivas para favorecer la adquisición de una competencia escrita en el alumnado. En este estudio se presenta el desarrollo de un sistema de tutoría inteligente, denominado CSRI-OL. El objetivo de este estudio es proporcionar una descripción de las principales características y componentes del Sistema de Tutoría Inteligente CSRI-OL, analizando críticamente tanto las principales dificultades que conlleva la adaptación de un complejo enfoque instruccional multi-componente como es la instrucción estratégica a un entorno virtual, como, las principales potencialidades que abre al campo científico y educativo el desarrollo de sistemas de tutoría inteligente como el que se presentaS

Technology-enhanced Personalised Learning: Untangling the Evidence

Technology-enhanced personalised learning is not yet common in Germany, which is why we have tasked scientists with summarising the current status of international research on the matter. This study demonstrates the great potential of technology in implementing effective personalised learning. Nevertheless, it has not been assessed yet whether the practical implementation actually works: Even in countries such as the U.S., which lead the way in using techology in classroom settings, hardly any evaluation studies have been done to prove the effectiveness of technology-enhanced personalised learning. In the light of the above, the authors make recommendations for actions to be taken in Germany to make best use of the potential of technology in providing individual support and guidance to students

Examining the Role of Linguistic Flexibility in the Text Production Process

abstract: A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the writing literature. Research suggests that higher quality writing is typically associated with decreased levels of text narrativity and readability. Although narrative elements may sometimes be associated with high-quality writing, the majority of research suggests that higher quality writing is associated with decreased levels of text narrativity, and measures of readability in general. One potential explanation for this conflicting evidence lies in the situational influence of text elements on writing quality. In other words, it is possible that the frequency of specific linguistic or rhetorical text elements alone is not consistently indicative of essay quality. Rather, these effects may be largely driven by individual differences in students' ability to leverage the benefits of these elements in appropriate contexts. This dissertation presents the hypothesis that writing proficiency is associated with an individual's flexible use of text properties, rather than simply the consistent use of a particular set of properties. Across three experiments, this dissertation relies on a combination of natural language processing and dynamic methodologies to examine the role of linguistic flexibility in the text production process. Overall, the studies included in this dissertation provide important insights into the role of flexibility in writing skill and develop a strong foundation on which to conduct future research and educational interventions.Dissertation/ThesisDoctoral Dissertation Psychology 201