Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

The Design of Learning Material for Poor Comprehenders: Lessons Learnt from Experts

TERENCE is an FP7 ICT European project that is developing an adaptive learning system for poor comprehenders and their educators. The learning material is made of stories and smart games for stimulating reading comprehension. The design of stories and smart games is also based on data collected from experts for the analysis of the context of use of the system, and is incrementally revised via evaluations of prototypes of stories and games, with domain experts of text comprehension or education as participants. In particular, since smart games are semi-automatically generated via artificial intelligence technologies, they contain mistakes that have to be fixed by experts of pedagogy before the games are given to learners. In this paper we focus on the design and evaluations of the TERENCE stories and smart games for poor comprehenders via lessons learnt with domain experts

Pedagogy-Driven Smart Games for Primary School Children

TERENCE is an FP7 ICT European project, highly multi-disciplinary, that is developing an adaptive learning system for supporting poor comprehenders and their educators. Their learning materials are stories and games, explicitly designed for classes of primary schools poor comprehenders, where classes were created via an extensive analysis of the context of use and user requirements. The games are specialised into smart games, which stimulate inference-making for story comprehension, and relaxing games, which stimulate visual perception and which train the interaction with devices (e.g., PC and tablet PC). In this paper we focus on how we used the pedagogical underpinnings and the acquired requirements to design the games of the system

The Use of New Technologies for Improving Reading Comprehension

Since the introduction of writing systems, reading comprehension has always been a foundation for achievement in several areas within the educational system, as well as a prerequisite for successful participation in most areas of adult life. The increased availability of technologies and web-based resources can be a really valid support, both in the educational and clinical field, to devise training activities that can also be carried out remotely. There are studies in current literature that has examined the efficacy of internet-based programs for reading comprehension for children with reading comprehension difficulties but almost none considered distance rehabilitation programs. The present paper reports data concerning a distance program Cloze, developed in Italy, for improving language and reading comprehension. Twenty-eight children from 3rd to 6th grade with comprehension difficulties were involved. These children completed the distance program for 15\u201320 min for at least three times a week for about 4 months. The program was presented separately to each child, with a degree of difficulty adapted to his/her characteristics. Text reading comprehension (assessed distinguishing between narrative and informative texts) increased after intervention. These findings have clinical and educational implications as they suggest that it is possible to promote reading comprehension with a distance individualized program, avoiding the need for the child displacements, necessary for reaching a rehabilitation center

The Learners' User Classes in the TERENCE Adaptive Learning System

Nowadays, circa 10% of 7-11 olds turn out to be poor comprehenders: they demonstrate text comprehension difficulties, related to inference making, despite proficiency in low-level cognitive skills like word reading. To improve the reading comprehension of these children, TERENCE, a technology enhanced learning project, aims at stimulating inference-making about stories. In order to design and develop the TERENCE system, we use a user centred design approach that requires an in depth study of the system's main end-users, namely, its learners and educators. This paper reports on the specification of the user classes for the TERENCE learners by means of user-centred design field studies, the resulting global system architecture, and an example use case of the system, with few related GUI's snapshots.European Commision (EC). Funding FP7/SP1/ICT. Project Code: 25741

iSTART: Interactive Strategy Training for Active Reading and Thinking

Interactive Strategy Training for Active Reading and Thinking (iSTART) is a Web-based application that provides young adolescent to college-age students with high-level reading strategy training to improve comprehension of science texts. iSTART is modeled after an effective, human-delivered intervention called self-explanation reading training (SERT), which trains readers to use active reading strategies to self-explain difficult texts more effectively. To make the training more widely available, the Web-based trainer has been developed. Transforming the training from a human-delivered application to a computer-based one has resulted in a highly interactive trainer that adapts its methods to the performance of the students. The iSTART trainer introduces the strategies in a simulated classroom setting with interaction between three animated characters—an instructor character and two student characters— and the human trainee. Thereafter, the trainee identifies the strategies in the explanations of a student character who is guided by an instructor character. Finally, the trainee practices self-explanation under the guidance of an instructor character. We describe this system and discuss how appropriate feedback is generated

Technology-based reading intervention programs for elementary grades: An analytical review

In modern societies, the role of reading is becoming increasingly crucial. Hence, any impairment to the reading ability can seriously limit a person's aspirations. The enormous importance of reading as an essential skill in modern life has encouraged many researchers to try and find more effective intervention approaches. Technology has been used extensively to assist and enhance literacy learning. This analytical review aims at presenting a comprehensive overview of the existing research on technology-based or technology-assisted reading interventions for elementary grades, between 2000 and 2017, along with analyzing various aspects of these studies. After extensive research, 42 articles have met the inclusion criteria, which have evaluated a total of 32 reading programs. The studies are classified into six categories of phonological awareness, phonics, vocabulary, comprehension, fluency, and multi-component. Each reading category begins with a brief introduction. Then, the content and instructional mechanisms of each program in the category is explained, alongside the outcome of its interventions. It is found that vocabulary interventions, as well as using mobile, tablet and other non-computer technologies are massively overlooked. Furthermore, a very limited number of programs focused on fluency, none of them addressed all its components. In addition, despite the required long-term practice for fostering fluency, the reviewed studies have an average intervention time shorter than other intervention categories. This paper provides researchers and solution developers with an extensive and informative review of the current state of the art in reading interventions. Additionally, it identifies the current knowledge gaps and defines future research directions to develop effective reading programs

The TERENCE Smart Games: Automatic Generation and Supporting Architecture

TERENCE is an FP7 ICT European project that is developing an adaptive learning system for supporting poor comprehenders and their educators. Its learning material are stories and games. The games are specialised into smart games, which stimulate inference-making for story comprehension, and relaxing games, which stimulate visual perception and not story comprehension. The paper focuses on smart games. It first shows the current prototypes, then it describes the TERENCE system architecture, thus it delves into the generation of smart games instances, by highlighting the role of the constraint-based module therein. Finally, it ends with short conclusions about the planned improvements.

Teaching reading literacy strategies through the intelligent tutoring system TuinLECweb

La presente Tesis Doctoral tiene como objetivo examinar la eficacia del tutor inteligente TuinLECweb para enseñar estrategias de competencia lectora y mejorar el rendimiento de los estudiantes en situaciones de lectura orientada a tareas. Estas situaciones de lectura son habituales en la sociedad actual (White, Chen y Forsyth, 2010) y hacen referencia al uso de información textual con un fin concreto. En el ámbito educativo es también habitual que los estudiantes tengan que usar la información de un texto para realizar alguna tarea, como responder preguntas. Estas situaciones de lectura implican procesos cognitivos y metacognitivos que son parcialmente distintos a aquellos implicados en la comprensión lectora, pues además de comprender lo que están leyendo, los lectores deben tomar una serie de decisiones estratégicas que requieren un alto nivel de auto-regulación (McNamara y Magliano, 2009; Rouet, 2006). La primera decisión está relacionada con la lectura inicial del texto, pues el lector debe decidir qué cantidad de texto leer, con qué detenimiento y de qué manera. La segunda decisión se encuentra relacionada con la identificación de las demandas de la tarea, proceso cognitivo que debe ir acompañado de una autorregulación de la comprensión de la misma. Una vez identificadas las demandas de la tarea, el lector debe decidir si dispone de la información necesaria para resolverla adecuadamente o debe consultar el texto. Si decide consultar el texto, el lector deberá localizar y procesar la información relevante para la tarea, proceso que también implica auto-regulación por parte del lector. Abundante investigación ha demostrado que los estudiantes que auto-regulan correctamente estas decisiones obtienen mejores resultados cuando responder preguntas usando información de textos (Cerdán y Vidal-Abarca, 2008; Mañá, 2011; Vidal-Abarca et al., 2010). Los resultados de los pasados informes PISA (2010, 2014) han derivado en un creciente interés por la búsqueda de metodologías de instrucción para mejorar la competencia lectora de los estudiantes. Sin embargo, adquirir y mejorar habilidades cognitivas complejas habitualmente requiere una enseñanza explícita, algo que no ha recibido demasiada atención en las aulas (Bjork, Dunlosky y Kornell, 2013; Ness, 2011). En respuesta a esta carencia, en las últimas décadas ha emergido una línea de investigación basada en el uso de sistemas tutoriales inteligentes (STI) para mejorar la comprensión lectora y el uso de estrategias de los alumnos (e.g., iSTART: McNamara, Levinstein y Boonthum, 2004; LoCoTex: Potocki, Ecalle y Magnan, 2013). Diversos metaanálisis y revisiones han concluido que los STI incrementan el aprendizaje en mayor medida que la enseñanza en el aula o que otros métodos de enseñanza tradicionales (Kulik y Fletcher, 2016; Ma, Adesope, Nesbit y Liu, 2014). En el ámbito de la lectura orientada a tareas, Vidal-Abarca y colaboradores, desarrollaron TuinLEC, un tutor inteligente para enseñan estrategias de competencia lectora mediante la enseñanza explícita, el modelado y la práctica guiada de las mismas (Vidal-Abarca et al., 2014). La eficacia de TuinLEC para mejorar la competencia lectora de los estudiantes ha sido demostrada en varios estudios, los cuales también fueron de utilidad para detectar las ineficiencias de esta primera versión y desarrollar una versión mejorada de TuinLEC (i.e., TuinLECweb), cuya eficacia es analizada en esta Tesis Doctoral. En el estudio 1 se analizó el efecto inmediato y a largo plazo de TuinLECweb para mejorar el rendimiento y las decisiones estratégicas de los estudiantes. Estas decisiones fueron registradas por el software Read&Answer (Vidal-Abarca et al., 2011) a través de un conjunto de índices de estrategias de auto-regulación, predictores del éxito en situaciones de lectura orientada a tareas. Asimismo, se exploró la eficacia de la intervención en estudiantes de sexto curso de Educación Primaria y primer curso de Educación Secundaria con diferentes niveles de comprensión lectora identificar el perfil de estudiante que obtiene mayor beneficio de TuinLECweb. Finalmente, se examinó la usabilidad de TuinLECweb, así como la satisfacción de los estudiantes con la herramienta y el nivel de aprendizaje percibido. Los resultados indicaron que los mayores beneficios fueron obtenidos por los estudiantes con menor nivel de comprensión, quienes incrementaron su rendimiento dos semanas después de la intervención, aunque no el uso de estrategias. Los alumnos de 1ºESO mejoraron su rendimiento después de TuinLECweb, pero esta mejora no se mantuvo en el seguimiento, mientras que la mejora de los alumnos de 6º no fue significativa. Sin embargo, este último mostró mayor satisfacción, usabilidad y aprendizaje percibido. A partir de los resultados obtenidos en el estudio 1, en el estudio 2 se acotó la muestra a estudiantes a 6º curso de Primaria, se incrementó el tamaño de la muestra y se incluyó un grupo de comparación, el cual recibió una intervención tradicional en el aula con un cuaderno de mejora de la comprensión lectora aplicado por el profesor. El objetivo principal era analizar la eficacia de TuinLECweb en comparación con una enseñanza tradicional para mejorar el rendimiento y las estrategias empleadas por los estudiantes en una situación de lectura orientada a tareas, tanto a corto como a largo plazo. Adicionalmente, se analizó la utilidad percibida de las estrategias implicadas en la lectura orientada a tareas. El estudio 2 pone su énfasis en identificar las características de los estudiantes que se benefician en mayor medida de una intervención con TuinLECweb, por lo que se exploró el papel moderador de nuevas variables individuales, además de la comprensión lectora, como el rendimiento académico, la utilidad percibida de las estrategias entrenadas en TuinLECweb y el empleo de las mismas en una situación de lectura orientada a tareas. Por otra parte, este estudio pretendía explorar el mecanismo de cambio de TuinLECweb. Los resultados indicaron que TuinLECweb resultó más eficaz para mejorar el rendimiento a largo plazo en lectura orientada a tareas que una instrucción tradicional, especialmente en aquellos estudiantes con un menor rendimiento académico y menor comportamiento de búsqueda. También se mostró eficaz para mejorar la auto-regulación de las decisiones de búsqueda y la percepción de utilidad de las estrategias. Ambas intervenciones mejoraron el proceso de búsqueda de los estudiantes, pero disminuyeron sus decisiones de búsqueda. Finalmente, TuinLECweb incrementó la utilidad percibida de las estrategias, lo que condujo a un incremento en el rendimiento de los estudiantes dos semanas después de la intervención. Ambos estudios contribuyen a incrementar la evidenciar empírica sobre la superioridad de los tutores inteligentes sobre otras formas de instrucción (Ma et al., 2014; Tamim et al., 2011; VanLehn, 2011), atribuida principalmente a la inmediatez de la retroalimentación y a la capacidad de adaptación al estudiante (Azevedo y Bernard, 1995; Sosa, Berger, Saw y Mary, 2011). Aunque TuinLECweb no logra incrementar el uso de algunas estrategias efectivas, como la estrategia de búsqueda, sí logra mejorar las habilidades metacognitivas de los estudiantes, su rendimiento y el valor que éstos otorgan a las estrategias. Asimismo, los resultados de ambos estudios permiten acotar el perfil de la población que mayor beneficio obtiene de una intervención con TuinLECweb, así como aproximarnos a una explicación sobre el mecanismo de cambio. El presente trabajo tiene importantes implicaciones para la práctica educativa dirigida a mejorar la competencia lectora de los estudiantes