Context-aware Assessment Using QR-codes

In this paper we present the implementation of a general mechanism to deliver tests based on mobile devices and matrix codes. The system is an extension of Siette, and has not been specifically developed for any subject matter. To evaluate the performance of the system and show some of its capabilities, we have developed a test for a second-year college course on Botany at the School of Forestry Engineering. Students were equipped with iPads and took an outdoor test on plant species identification. All students were able to take and complete the test in a reasonable time. Opinions expressed anonymously by the students in a survey about the usability of the system and the usefulness of the test were very favorable. We think that the application presented in this paper can broaden the applicability of automatic assessment techniques.The presentation of this work has been co-founded by the Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Mining Web-based Educational Systems to Predict Student Learning Achievements

Educational Data Mining (EDM) is getting great importance as a new interdisciplinary research field related to some other areas. It is directly connected with Web-based Educational Systems (WBES) and Data Mining (DM, a fundamental part of Knowledge Discovery in Databases). The former defines the context: WBES store and manage huge amounts of data. Such data are increasingly growing and they contain hidden knowledge that could be very useful to the users (both teachers and students). It is desirable to identify such knowledge in the form of models, patterns or any other representation schema that allows a better exploitation of the system. The latter reveals itself as the tool to achieve such discovering. Data mining must afford very complex and different situations to reach quality solutions. Therefore, data mining is a research field where many advances are being done to accommodate and solve emerging problems. For this purpose, many techniques are usually considered. In this paper we study how data mining can be used to induce student models from the data acquired by a specific Web-based tool for adaptive testing, called SIETTE. Concretely we have used top down induction decision trees algorithms to extract the patterns because these models, decision trees, are easily understandable. In addition, the conducted validation processes have assured high quality models

Towards Computerized Adaptive Assessment Based on Structured Tasks

Tvarožek, J., Kravčík, M., & Bieliková, M. (2008). Towards Computerized Adaptive Assessment Based on Structured Tasks. In W. Nejdl et al. (Eds.), Adaptive Hypermedia and Adaptive Web-Based Systems (pp. 224-234). Springer Berlin / Heidelberg.In an attempt to support traditional classroom assessment processes with fully computerized methods, we have developed a method for adaptive assessment suitable for well structured domains with high emphasis on problem solving and capable of robust continuous assessment, potentially encouraging student’s achievements, reflective thinking, and creativity. The method selects problems according to the student’s demonstrated ability, structured task description schemes allow for a detailed analysis of student’s errors, and on-demand generation of task instances facilitates independent student work. We evaluated the proposed method using a software system we had developed in the domain of middle school mathematics.This work was partially supported by the Cultural and Educational Grant Agency of the Slovak Republic, grant No. KEGA 3/5187/07 and the TENCompetence Integrated Project that is funded by the European Commission’s 6th Framework Programme, priority IST/Technology Enhanced Learning. [http://www.tencompetence.org

Dynamic computerized-adaptive assessment of reading processes: Incremental validity on text comprehension

This study explores the predictive and incremental validity of the Dynamic Computerized Adaptive Reading Processes Assessment Device (EDPL-BAI). This battery has 38 tasks organized in 6 modules to assess different processes related to reading comprehension (e.g. phoneme-grapheme association, executive functions, metacognitive processes). Method: A total of 1336 Chilean students from 3rd to 6th grade (45% females) from 12 public urban and rural schools participated in a longitudinal study consisting of three assessment cycles. On the first cycle, the students were assessed with a standardized reading comprehension test (CL-PT), the Raven Progressive Matrices Test (PMR), and the complete poll of items were calibrated in a non-dynamic version of EDPL-BAI. On the second cycle, seven months after, a sub sample of 1068 students were administered the adaptive and dynamic version of the EDPL-BAI (graduated prompts were displayed after wrong responses), while the remainder 268 students were assessed with the non-dynamic version of EDPL-BAI, and for all the students a pre and post-test (using selected items from EDPL-BAI), CL-PT and PMR were administered. Finally, at the third cycle, four month after, the non-dynamic version of EDPL-BAI and CL-PT were administered to the complete sample. Results and Conclusions: Multiple CFAs were conducted to determine the factorial structure of the EDPL-BAI, and a final model of 6 factors was retained. Predictive and incremental validity of the EDPL-BAI was explored with SEM analysis. The dynamic and non-dynamic versions of the EDPL-BAI were good predictors of reading comprehension. The dynamic version showed incremental validity over the non-dynamic version. Furthermore, graduated prompts predicted reading comprehension performanc

Deep Learning Approach for cognitive competency assessment in Computer Programming subject

This research examines the competencies that are essential for an lecturer or instructor to evaluate the student based on automated assessments. The competencies are the skills, knowledge, abilities and behavior that are required to perform the task given, whether in a learning or a working environment. The significance of this research is that it will assist students who are having difficulty learning a Computer Programming Language course to identify their flaws using a Deep Learning Approach. As a result, higher education institutions have a problem with assessing students based on their competency level because; they still use manual assessment to mark the assessment. In order to measure intelligence, it is necessary to identify the cluster of abilities or skills of the type in which intelligence expresses itself. This grouping of skills and abilities referred to as "competency". Then, an automated assessment is a problem-solving activity in which the student and the computer interact with no other human intervention. This review focuses on collecting different techniques that have been used. In addition, the review finding shows the main gap that exists within the context of the studied areas, which contributes to our key research topic of interest

Adapting the automatic assessment of free-text answers to the students

In this paper, we present the first approach in the field of Computer Assisted Assessment (CAA) of students' free-text answers to model the student profiles. This approach has been implemented in a new version of Atenea, a system able to automatically assess students' short answers. The system has been improved so that it is now able to take into account the students' preferences and personal features to adapt not only the assessment process but also to personalize the appearance of the interface. In particular, it is now able to accept students’ answers written in Spanish or in English indistinctly, by means of Machine Translation. Moreover, we have observed that Atenea’s performance does not decrease drastically when combined with automatic translation, provided that the translation does not reduce greatly the variability in the vocabulary

Marshland Colonization in Acadia and Poitou during the 17th Century

This article compares marshland colonization in Acadia and France during the 17th century.  It begins with an analysis of why  the initial attempts to colonize marshlands failed.  It then compares the later, successful initiatives at Port Royal, in Acadia, and the Poitevin Marsh, in France.  Although they had very different objectives and tackled very different environmental challenges, both groups effectively organized their activities and used innovation in adapting old techniques. What made Acadian marshland farming distinctive was its small scale and its dispersed, decentralized nature.   Both initiatives demonstrate how successful marshland colonization was a profoundly local endeavour.Cet article compare la colonisation des terres marécageuses en Acadie et en France au cours du 17e siècle. Il s’ouvre sur une analyse des raisons pour lesquelles les premières tentatives en vue de coloniser les marais échouèrent. Il compare ensuite les tentatives fructueuses effectuées plus tard à Port-Royal, en Acadie, et dans le Marais poitevin, en France. Malgré les objectifs bien différents qu’ils poursuivaient et les défis différents posés par l’environnement, les deux groupes organisèrent leurs activités avec efficacité et firent preuve d’innovation en adaptant de vieilles techniques. Ce qui fit la particularité de la culture des marais en Acadie, c’est sa petite échelle et son caractère dispersé et décentralisé. Les deux initiatives démontrent comment la colonisation des terres marécageuses était une entreprise profondément locale

Implementation of a library of interactive items for SIETTE

El sistema SIETTE es una plataforma que permite realizar tareas de evaluación de forma automática en entornos virtuales de aprendizaje. Su funcionamiento se organiza en torno al concepto de Tema, subtema y pregunta. Los tipos de preguntas que pueden realizarse en este sistema pueden ser desde una selección múltiple o una respuesta abierta a tipos más complejos que pueden ir añadiéndose al sistema con desarrollos adicionales de programación según diversas necesidades. A estos últimos se les denomina ítems externos. En este trabajo se ha ampliado la biblioteca de ítems interactivos de la que dispone la plataforma SIETTE. Para ello se ha profundizado en el concepto de aprendizaje online y de usabilidad. Concretamente, se han implementado tres ítems. El primero, denominado Emparejamiento, busca trabajar y estudiar la capacidad del alumnado para relacionar conceptos de un mismo tema y ser capaces de ver patrones y diferencias en estos. El segundo ítem, denominado Etiquetado de Imagen, consiste en dar nombre a los elementos señalados en una determinada imagen. Este ítem busca trabajar y evaluar la capacidad del alumnado de reconocer los elementos de un determinado tema de manera visual. El tercer ítem, Selección de Área, comparte el mismo objetivo que Etiquetado de Imagen, pero con la diferencia de que el alumno recibe los nombres de los elementos y debe señalar dónde se encuentran en la imagen. Estos ítems se han configurado para su integración en SIETTE y su uso en alumnos reales. Esto permitirá mejorar las opciones de los docentes a la hora de preparar cursos de evaluación automática para conocer el nivel de comprensión de un tema o para opciones de autoaprendizaje y refuerzo de la materia impartida

An Algorithm for Generating Gap-Fill Multiple Choice Questions of an Expert System

This research is aimed to propose an artificial intelligence algorithm comprising an ontology-based design, text mining, and natural language processing for automatically generating gap-fill multiple choice questions (MCQs). The simulation of this research demonstrated an application of the algorithm in generating gap-fill MCQs about software testing. The simulation results revealed that by using 103 online documents as inputs, the algorithm could automatically produce more than 16 thousand valid gap-fill MCQs covering a variety of topics in the software testing domain. Finally, in the discussion section of this paper we suggest how the proposed algorithm should be applied to produce gap-fill MCQs being collected in a question pool used by a knowledge expert system