EDUCATIONAL MODELS FOR ONLINE ...

EDUCATIONAL MODELS FOR ONLINE ASSESSMENT Martin Lesage, Martin Riopel, Gilles Raîche, Komi Sodoke et Sébastien Béland Faculty of Education Université du Québec à Montréal, P.O. Box 8888, stn. Centre-ville, Montréal, QC H3C 3P8 (514) 987-3000 extension 8982 [email protected], [email protected]; [email protected]; sodoke.komi_sepeli @courrier.uqam.ca; [email protected] ABSTRACT Research on Internet use for distance learning and counselling seems to prove that results are the same when comparing traditional distance learning and counselling versus its online counterpart. A lot of work and efforts had been invested by education institutions to convert printed course material in electronic format. Therefore, future work is still to be done to improve online assessment that is often neglected during online course implementation. This type of assessment actually consists mainly in a combination of true-false and multiple choice questions. The aim of the actual research is to expand the online assessment field with the development of online complex assessment tasks in authentic context to provide an online assessment more complex that a simple presentation of multiple choice questions. These complex assessment tasks could be in collaborative mode including open questions, portfolios, scenarios, projects assessment types performed in collaborative mode allowing multiple students to realize the tasks and multiple supervisors assessing the students. The assessors could even communicate with the students while they perform the tasks to issue comments or to correct them. The present research wants to develop education and assessment models to expand the domain and to provide answers to the problematic. A first type of models will concern the development of assessment and educational models needed for the development of complex assessment tasks in collaborative mode. A second type of models will be data models needed to code the assessment tasks in XML code. The third type of models will be a user interface model enabling the display of complex assessment tasks in collaborative mode on the user’s computer display or terminal.

I. PROBLEMATICS The actual research places itself in the discipline of distance assessment over the Internet. This type of assessment had opened research domains in the education and learning systems fields (Rudestam & Schoneholtz-Read, 2002, p.4; Nacro, 2000, p. 2). Some authors, as Andrews & Haythornthwaite (2007, p. 16) are stating that learning modes and techniques not supported by Internet are now obsolete for higher education. The passage of traditional learning to distance learning over the Internet needs a revision of pedagogy and learning concepts (Rudestam & Schoneholtz-Read,

2

2002, p.4). Willing to comply with computer networks and Internet technology, many educational institutions have started to convert their courses from paper to electronic format. In many cases, these electronic courses are only a sequence of electronic pages displaying text (Nacro, 2000, p. 2). This project wants to improve formative and summative distance assessment systems design that could also be adaptive. User interfaces of these systems must be ergonomic, rich and user friendly. On opposite case, hard to learn user interfaces could distract or scare the user and hinder his learning process (Andrews & Haythornthwaite, 2007, p. 10; Burns & Capps, 1988, p. 12; Petit, 2006, p. 64-65; Schneiderman, 1992, p.53; Nacro, 2000, p. 15). There is also a need to standardise these learning systems and interfaces (Schneiderman, 1992, p. 10). The standardization process is realized to improve consistency and portability. Consistency refers to operations, sequences, terms, screen standards, colors and font normalization while portability is the ability to convert data and to share user interface among many hardware and software platforms (Schneiderman, 1992, p.11). To improve actual assessment systems, the present research will improve their design with the realisation of an assessment task presentation website with a research and development methodology (« R&D ») that will contribute to develop educational models. In the particular case of learning, the assessment activities used to grade the learner could be synthetized in tasks to perform (Nacro, 2000, p. 2). These assessment tasks situate themselves in an authentic context while evaluating competencies and skills. This project will provide answers to the questions stated in the problematic by the development of three types of models: assessment and educational models needed to implement the use of complex assessment tasks in course programs; a data model needed to code and store the assessment tasks in a XML code standardized format; and also a user interface model enabling software applications to display assessment tasks in collaborative mode. These models will provide answers to the research

3

question: « How to improve the data representation of learning and assessment material in an efficient online education context? ».

II. THEORETICAL BACKGROUND This research project places itself in the artificial intelligence and education disciplines. The project’s educational aspects are assessment tasks, online education and educational models fields. The artificial intelligence aspects are data structures, data models and user interface models. This section introduces the research project theoretical background and related work.

2.1. Assessment tasks concept The Rhode Island Department of Elementary and Secondary Education (RIDE, 2008) defines assessment tasks as « authentic and rigorous activities that relate to the instructional outcomes and allow students to demonstrate what they know and can do. These may include oral and written responses, problem solving, journals, and exhibitions. They determine how well students are learning, as well as how well they have attained the content expectations. Assessment tasks need to be integrated throughout the curriculum to provide on-going and comprehensive information about each student’s learning ».

2.2. Online education concept A complete definition of online education at formal, axiologic and praxiologic levels is stated by Ponmelil (2008): « Online education is a flexible learning through

4

educational web sites such as those offering learning scenarios, worksheets and interactive exercises ».

2.3. Data models A model is a verbal, graphical or mathematical representation of process, objects, systems or phenomenon that could be interrelated and used to simplify a reality (Larousse, 2008, p.653; L’Écuyer, 1990, p.3; Thinès & L’Empereur, 1984, p. 603). The actual research needs to produce data models. These data models will be based on data structures designed for the conversion of complex assessment tasks into electronic format. The aim of the data conversion is to store the assessment tasks on Internet servers coded into distance learning standards. These electronic format converted assessment tasks on Internet servers will form databases that will be accessed by distance learning websites having assessment capabilities. The assessment tasks standardization will enable the tasks to be accessible by many applications without conversion into different formats. The conversion will then save time and money. The data structures containing the assessment tasks will be XML coded electronic files and these tasks could be considered as items according to the Items Response Theory (IRT). The XML acronym significates eXtensible Markup Language. It is a language made of programmer defined tags enabling them to create the fields and records of databases. Many database management systems (DBMS) on the Internet are now built in XML. This language could also be used to define learning

and

evaluation

objects.

As

previously

stated,

assessment

tasks

standardization should be done according XML based distance learning standards enabling them to be retrieved on any distance learning website. On the actual research project, many distance learning standards have been studied as Dublin Core/DCMI (Dublin Core Metadata Initiative), IEEE LTSC LOM (Learning Object Metadata), AICC/CMI (Courseware Management Interface), ADL/SCORM (Sharable Context

5

Object Reference Model) and also QTI-IMS (Instructional Management Systems). The Dublin Core, SCORM, LOM and AICC/CMI distance learning standards doesn’t have

assessment

capabilities

while

IMS-QTI

does.

Despite

its

multiple

functionalities, this last distance learning standard could not model item parameters of the item response theory and also user interface characterization parameters. The implementation of these two types of parameters to enhance the IMS-QTI standard will be one of the goals of the project. This will enable the XML translation of text, problems, date, user interface parameters management, user screen content management, answers encoding, education institutions course material formatting standards and also the collaborative mode implementation.

2.4. User interface models Cockton (1990, p. 107) have studied user interface models and stated that « a model is a representation of a structure for an interactive system » and that structure must « be adapted for a specific interactive application » (Cockton, 1990, p. 107). This statement is completed by Kass & Finn (1991, p. 112) affirming that user interface modeling « is an important component of many information systems leading them to a more intelligent interaction » and create an improvement « where the system wants to adapt its behaviour to the user’s responses while communicating with them ». A user interface model can be associated with a mechanism or an algorithm based on data structures. This model could be represented by a plan, a schema or a computer program. An important fact is that even though this model is a simplification, it must be rigorous enough to represent many of the theories relative to the case (Van Der Veer, Green, Hoe & Murray, 1988). A user interface model defines relations between anthropometric and biomechanical models regarding user interface ergonomics (Kroemer, Snook, Meadows & Deutsch, 1988, p. 43).

6

According to Norman (1986, p. 47), there are three types of user interface models. The first type is design models or conceptual models that are the computer system’s plans to be developed by the computers scientists. The second type is mental models or user’s models allowing the user to develop a mental image or representation of the software application used. The third type is the system image resulting of the application development that is the inclusion of documentation and instructions. Wahlster (1991, p. 48) states that the mental or user model « is a knowledge source regrouping explicit statements regarding all aspects that the user must know about the communication protocols with the user interface ». The mental model developed by the user is created with is understanding of the system’s image resulting of his manipulations of the user interface (buttons, menus, windows, commands, help functions, etc.) and of the documentation (instructions, user’s manual, error messages, etc.) (Norman, 1986, p. 47). Bayman & Mayer (1984, p.192) concludes that these models are « a metaphor made of components and machine’s rules of operation ». These models are very important « when the user must determine the actual state of the machine or to choose a sequence of commands producing a predetermined result ». Mental model is an important resource for informal learning and software ambiguity detection where hypothesis are tested and proved by using the application (Brown, 1986). This model provides predictive and explicative capabilities enabling interaction understanding (Norman, 1983, p. 92). Kass & Finn (1991, p. 114) states that mental model «provides a generalization of the interactions and could be used with multiple communication modes as graphics, photos, images, menus and natural language (words and sentences) used with knowledge based systems ». Software design methods isolating user interface code from application code is a fundamental data structure encapsulation principle supported by the whole software engineering community. Finally, Caroll & Olson (1988) defines mental model as « knowledge about system operations, components, intern process and their relations » (Caroll & Olson, 1988, p. 47).

7

The user interface « provides the image definition of an interactive system while the software application controls the data processing » (Coutaz, 1990. p. 137). Most of models and software design tools are based on « the analogy of an interaction with a user and a software application that is similar to a conversation or a dialog between two human persons. The conversation succeed and the dialog is establish when the two communicators are using a common language » (Coutaz, 1990. p. 139). This research project needs to develop user interface models defining display process for assessment tasks. These models will define software systems being Web sites able to display assessment tasks in collaborative mode. They will be also used to define user interface components as menus, windows, buttons and also screen management for the assessment tasks collaborative mode implementation. They will finally define assessment tasks real time supervising mode by teachers or system administrators. These assessment tasks will be stored on Internet servers according to distance learning standards enabling them to be displayed on many software and hardware applications.

2.5. Educational models The models concept includes to a large extent « every mental or material representation of a real system, expressed in verbal, graphical or mathematical form » (Mialaret, 1990, p.36). A model could also be « a simplified formal theoretical representation of a complex reality used to facilitate its understanding and duplication ». These models have seldom the representation of physical systems, axioms and simulation that could « establish heuristic methods in humanities » (Thinès & L’Empereur, 1984, p. 603). Gohier (1990) states that « the concept of models in the education discipline is related to the wide and misused epistemology of education’s field », this field being part of the humanities’ epistemology discipline.

8

According to Legendre’s dictionary of education (Legendre, 2005, p. 892), an educational model is « an explicit and comprehensive representation of the education field » including « multiple pedagogical models ». Legendre (2005, p. 892) also provides a pedagogical models definition being « a representation of the pedagogical situation » and a « set of directions for educational environment and activities design». These pedagogical models could include a theoretical framework, goals and global objectives (Legendre, 2005, p. 892). Charland (2008, p. 152) states that « all education process must obey or be represented by models » representing a teaching experience. Educational models have two aspects: a theoretical aspect « defining a vision of the human being, the society or education field’s general aspect » and a praxeologic aspect « presenting pedagogical situation’s main characteristics». (Charland, 2008, p. 152). Raby & Viola (2007, p. 38) are defining teaching models as « a combination of strategies that a teacher could use to help his students in their process of learning ». These models are based on socioconstructivist, cognitivist, humanist and behaviorist theories. The teaching models based on socioconstruvistic theories is project based learning (Raby, 2007, p. 41), models based on cognitivism theories is strategic teaching (Viola, 2007, p. 136), models based on humanist theories are open pedagogy and actualizing pedagogy (Beaudry, 2007, p. 189) and models based on behaviorism theories is direct teaching (Théorêt, 2007, p. 208). The previous models are teaching models. The actual project is in the assessment field. One of the goals to reach in the actual project is to develop assessment models or education models in the assessment field concerning the use of assessment tasks. The models that will be developed in this research project will include a theoretical framework regarding complex assessment tasks in authentic context and also praxeologic theories concerning distance assessment using collaborative mode Internet software application.

9

2.6. Related work The aim of the present research project is collaborative complex assessment tasks presentation in authentic context. The displaying sequence of these tasks could be adaptive or not. In this project, the assessment tasks are coded in XML language. The XML coding of the assessment tasks will be done in IMS-QTI distance learning standard according to its previously cited advantages. The actual research concerning models and distance assessment resulting from the literature review has identified some examples of distance assessment models and XML applications displaying assessment tasks in adaptive or sequential manner. Our literature review found some existing artificial intelligence models regarding the presentation of learning tasks with user interfaces as GOMS (Goals – Operators – Methods – Selection rules) model and WAGLE (Web Adaptable and Generic Learning Environment) system. The GOMS model creates a representation of learning tasks with four information parameters: user’s interaction goals, user’s cognitive operations, operations sequencing methods for goal achievement and user’s rule selection related to methods used for goal achievement (Gimnich, 1991, p.117). The WAGLE system is an Internet based distance learning application including a learning representation model and acquired knowledge assessment capabilities (Nacro, 2000, p.17). It should be accurate and useful to adapt these models in the present educational research enabling them to create adaptive user interface capable to display authentic context complex assessment tasks. Other education research groups have developed similar projects to implement assessments process onto online learning applications: SIETTE (Conejo, Guzmàn, Millàn, Trella, Pérez-De-La-Cruz & Rìos, 2004), QTIeditor (Pacurar, Trigano & Alupoaie, 2005), CosyQTI (Lalos, Retalis & Psaromiligkos, 2005) and PersonFIT (Sodoke, Nkambou, Raîche, Riopel & Lesage, 2007). The three last cited applications are using IMS-QTI standard to encode their questions. Another interesting distance assessment application is the RATH (Relational Adaptive Tutoring) system using

10

knowledge space theory (Hockemeyer & Albert, 1999; Hockemeyer, Held & Albert, 1997). SIETTE and PersonFIT applications are using an assessment process based on item response theory but their designer didn’t implement adaptive user interfaces for these applications. A similar project to our actual research is developped by Gerbé, Raynauld & Beaulieu (2006) and named « Sac d’école électronique » (electronic schoolbag). Tis project is sponsored by University of Montréal’s « Maison des technologies de formation et d’apprentissage Roland-Giguère » (MATI) (http://www.matimtl.ca) [Roland Giguère’s house of learning and formation]. The aim of this project is to define a XML based distance learning standard to encode learning and assessment situations following a competency assessment approach. This project models learning and assessment situation according to the Normetic standard based on the LOM distance learning standard instead of IMS-QTI used in our research. The « Electronic scoolbag » project models learning and assessment situation parameters as : situation’s generalities (titles , authors, summary of the problem, standard to attain and marking instructions), discipline (littérature, grammar, sciences, philosophy, mathematics, arts & crafts, etc.), types of learners (students, military personnel, workers, etc.), type of tasks (homework, exam, portfolio, project, etc.), concepts to learn, skills and competencies to acquire, assessment criteria, teaching modes and also learning activities included in the situation.

III. METHODOLOGY The research methodologies must be analyzed in the actual research project to develop educational, user interface and data models used to display complex assessment tasks in authentic context on distance learning Websites. The project realization will first need to develop as assessment tasks presentation software that will be used to induce models. The development of a software application given to

11

students to enhance assessment is here considered to be a pedagogic tool. The development and testing process of the pedagogic tool will be used to produce educational theories represented into educational models. The previously stated problematic and the study of educational research methodologies concludes that pedagogic tools development and classroom implementation belongs to the Research and Development (R & D) methodology. The Research and Development methodology also named by the abbreviation R&D, is similar to the engineering discipline products design and development process (Van der Maren, 2003, p. 108). This methodology’s goals are to apply high end knowledge and technology by the development of innovating pedagogic tools (Loiselle, 2001, p. 78; Legendre, 2005, p. 1140). This methodology’s aim is to modify educational actions and teaching strategies by the development of the latest technology pedagogic tools (Van der Maren, 2003, p. 108). This methodology supports feasibility analysis in the « development of solutions for practical problems» (Loiselle, 2001, p. 78) with « tools that could influence pedagogical practices » (Loiselle, 2001, p. 77). The development process « is the building process of a product » while the Research and Development process « wants to analyze the experiences of design and development process to induce new knowledge » (Loiselle, 2001, p. 89). Regarding the education discipline, this research methodology wants to bring solutions by the design and development of pedagogic tools. The Research and Development methodology is a kind of action research where the researcher’s action is the development and implementation of a pedagogic product or application (Gagné, Lazure, Sprenger-Charolles et Ropé, 1989, p. 55). This process wants to improve pedagogic actions instead of to establish scientific proofs (Loiselle, 2001, p. 94). The aim of the Research and Development method is the analysis of pedagogic tools used to induce knowledge (Loiselle, 2001, p. 87) to modify educational actions or pedagogic practices. The actual research project is based on the development of a distance assessment software application that will display assessment tasks stored in database

12

management systems on Internet servers. The Research and Development method is the only one in the education discipline based on educational products development. This method is the one that adapts itself the best to the actual research project by its educational tool and theory development capabilities. This methodology is based on an interpretative epistemology and facilitates the use of qualitative methods (Loiselle et Harvey, p. 48) for results analysis. This project wants to collect data with qualitative methods by observation and evaluation grids according to Schneiderman’s (1987, p. 61) eight golden rules of user interface design. The data will be produced by the observation of military personnel performing complex assessment tasks on distance learning Web sites. The evaluation grids will be filled while observing and interviewing the military personnel. The assessment criteria will be based on user interface’s quality, the assessment tasks and menu’s accuracy, help function’s usefulness, communication and collaborative work’s easiness. Another assessment’s aspect will be realized by open questions asked to the military personnel to verify if they like the user interface and the overall application.

IV. PRELIMINARY RESULTS The actual research project based on a Research and Development methodology is actually at his beginning. The models’ theoretical framework supporting the research is now defined. The programming of the Internet software application displaying the assessment tasks have now begun because this Web site is the pedagogical tool developed in the Research and Development process.

4.1. Proposed educational model Figure 1 illustrates an educational model defining educational strategies for distance assessment based on complex assessment tasks in authentic context. The aim

13

of this model is to show teachers electronic format course conversion to place course material in distance learning Web sites. The model also shows teachers how to divide course material into teaching points. Once the teaching program or course material is divided into small teaching points, these teaching points are now coded in XML language to be stored into distance learning Web sites databases. The complex assessment tasks in authentic context are now built with the combination of XML coded teaching points to assess competencies or objectives according to courses curriculum’s criteria. With this model, teachers’ educational actions are now oriented toward distance assessment using complex assessment tasks in authentic context.

Figure 1. Educational models for assessement tasks implementation

14

4.2. Distance assessment Web site development Figure 2 illustrates the actual project complex assessment tasks data entry user interface. Assessment tasks data is converted in XML language and stored onto the application’s Web site database management system

Figure 2. Assessment tasks data entry interface

CONCLUSION The actual research project is based on a Research and Development methodology with the design of a distances assessment Web site application and to induce theories synthesized into models. The general aspect of models presented in the actual research includes user interface, educational and data models. One of the main goals of this project is to provide teachers educational models enabling them to elaborate teaching strategies based on complex assessment tasks in authentic context. These complex assessment tasks are oriented on learning scenarios, interactive exercises and also open questions.

15

BIBLIOGRAPHY AND REFERENCES ADL/SCORM. Sharable Context Object Reference Model (SCORM). (2009). Accès: http://www.adlnet.org AICC-CMI. Aviation Industry CBT Committee (AICC)-Courseware Management Interface (CMI). (2009). Accès: http://www.aicc.org Andrews R. et Haythornthwaite, C. (2007). Introduction to E-Learning. Dans Andrews R. et Haythornthwaite, C. (Dirs.). The SAGE Handbook of E-Learning Research (p. 1-52). Californie: SAGE Publications Inc Bastien, J. M. C. et Scapin, D. (1993). Ergonomic Criteria for the Evaluation of HumanComputer interfaces [En ligne]. Institut National de Recherche en Informatique et en Automatique. Accès: http://www.inria.fr Bayment, P. et Mayer, R. E. (1984). Instructional Manipulation of User’s Mental Models for Electronic Calculators. International Journal of Man-Machine Studies, 20, pp 189-199. Beaudry, N. (2007). Pédagogie ouverte et pédagogie actualisante. Dans C. Raby et S. Viola (Dirs.), Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie (p. 189-196). Montréal : Les Éditions CEC inc. Brown, J. S. (1986). Cognitive engineering. Dans D. A. Norman et S. W. Draper (Dirs.), User Centered System Design : New Perspectives on Human-Computer Interaction (p. 457-486). Hillsdale, New Jersey : Lawrence Erlbaum Associates. Burns, H. L. et Capps, C. G. (1988). Foundations of Intelligent tutoring systems : An introduction. Dans Polson, M. C. et Richardson J. J. (Dirs.) Foundations of intelligent tutoring systems. Hillsdale : Lawrence Erlbaum Associates, Inc. Caroll, J. M. et Olson, J. R. (1988). Mental models in Human-Computer Interaction. Dans M. Helander (Dir.), Handbook of Human-Computer Interaction (p. 45-65). Nrw-York : North-Holland (Elsevier Science Publishers). Charland, P. (2008). Proposition d’un modèle éducationnel relatif à l’enseignement interdisciplinaire des sciences et de la technologie intégrant une préoccupation d’éducation relative à l’environnement. Thèse de doctorat inédite, Université du Québec à Montréal (UQAM). Cockton, G. (1990). Introduction. Dans G. Cockton (Dir), Engineering for Human-Computer Interaction (p. 107-111). New-York : Elsevier Science Publishing Company Inc. Conejo, R., Guzmàn, E., Millàn, E.,Trella, M., Pérez-De-La-Cruz, J. L. et Rìos, A. (2004). SIETTE : A Web Based Tool for Adaptive Testing. International Journal of Artificial Intelligence in Education, 14, 29-61. Coutaz, J. (1990). Architecture models for interactive software: failures and trends. Dans G. Cockton (Dir), Engineering for Human-Computer Interaction (p. 107-111). New-York : Elsevier Science Publishing Company Inc. Dolbec, A. (2003). La recherche-action. Dans B. Gauthier (Dir.), Recherche sociale : De la problématique à la collecte de données (4ième Édition) (p. 506-540). Québec : Presses de l’Université du Québec. Dolbec, A. et Clément, J. (2004). La recherche-action. Dans T. Karsenti et L. Savoie-Zajc (Dirs.), La recherche en éducation: étapes et approches (p. 181-208). Sherbrooke: Éditions du CRP. Dublin Core/DCMI (Dublin Core Metadata Initiative). (2009). Accès: http://dublincore.org

16

Gagné, G., Lazure, R., Sprenger-Charolles, L. et F. Ropé. 1989. Recherches en didactique et acquisition du français langue maternelle. Tome 1: Cadre conceptuel, thésaurus et lexique des mots-clés. Bruxelles: De Boeck-Westmael. Gerbé, O. Raynauld, J., et Beaulieu, M. (2006). Vers un standard de la description des situations d’apprentissage et d’évaluation [En ligne]. Accès : http://neumann.hec.ca/chaireteag/ColloqueSc%E9nario2007RaynauldFinal.pdf Gimnich, R. (1991). Usability Engineering and User Interface Management. Dans Duce, D.A., Gomes, M. R., Hopgood, F.R.A., Lee, J, R. (Dirs). User Interface Management and Design. New-York: Springer-Verlag. Gohier, C. (1990). Biologie et éducation : le paradigme latent. Dans l’Association Internationale de Pédagogie Expérimentale de langue Française section Canadienne (Dir.), Les modèles en éducation (p. 3-11). Montréal : Édition Noir sur Blanc. GTN-Quebec (2008). XML Normetic. [En ligne] Accès: http://www.normetic.org Hockemeyer, C. et Albert D. (1999). The Adaptive Tutoring System RATH : a Prototype. Workshop Interactive Computer aided Learning: Tools and Applications (ICL99). Hockemeyer, C., Held, T. et Albert D. (1997). RATH A Relational Adaptive Tutoring Hypertext WWW-Environment Based on Knowledge Space Theory. Proceedings of the Fourth International Conference on Computer Aided Learning in Science and Engineering (CALISCE`98 ), 417-423. IEEE LTSC LOM (2007). Learning Object Metadata. [En ligne] Accès: http://ieeeltsc.org IMS Global Learning Consortium, Inc (2007). QTI standard [En ligne]. Accès: http://www.imsglobal.org/question/ Kass, R. et Finn, T. (1991). User and discourse models for multimodal communication. Dans J. W. Sullivan et S. W. Tyler (Dirs.), Intelligent user interfaces (p. 111 – 128). NewYork : ACM Press (Addison-Wesley Publishing Company). Kroemer, K., Snook, S., Meadows, S., et Deutsch, S. (Dirs.) (1988). Ergonomic Models of Anthropometry, Human Biomechanics, and Operator-Equipment Interfaces : Proceedings of a Workshop (p. 43-67). Washington, D.C. : National Academy Press. Lalos, P., Retalis, S. et Psaromiligkos, Y. (2005) Creating personalised quizzes both to the learner and to the access device characteristics: the Case of CosyQTI [En ligne]. Accès : http://wwwis.win.tue.nl/~acristea/AAAEH05/papers/3camera%20readyCoSyQTI.pdf L’Écuyer, J. (1990). Les modèles en sciences de l’éducation. Dans l’Association Internationale de Pédagogie Expérimentale de langue Française section Canadienne (Dir.), Les modèles en éducation (p. 3-11). Montréal : Édition Noir sur Blanc. Legendre, R. (2005). Dictionnaire actuel de l’éducation (3è ed.). Montréal : Guérin. Le petit Larousse Illustré (2008). Paris : Les éditions Larousse. Lesage, M. (2007). Moteur d’administration en ligne des apprentissages basé sur des normes formelles d’objets d’évaluation. Communication présentée au 75è Congrès de l’ACFAS, Trois-Rivières, Québec. Lesage, M., Raîche, G., Riopel, M. et Sodoke, K. (2007). Interfaces Modelization in Computerized Adaptive Testing (CAT) Context for Learning Optimization. E-Learn 2007, 342-351. Loiselle, J. (2001). La recherche développement en éducation: sa nature et ses caractéristiques. Dans M. Anadón et M. L'Hostie (Dirs), Nouvelles dynamiques de recherche en éducation (p. 77-97). Québec: Les Presses de l'Université Laval.

17

Loiselle, J. et Harvey, S. (2007). La recherche développement en éducation : fondements, apports et limites. Recherches qualitatives, 27 (1), 40-59. MATI (2008). Maison des technologies de formation et d’apprentissage Roland-Giguère. [En ligne] Accès: http://www.matimtl.ca Mialaret, G. (1990). Les modèles en sciences de l’éducation. Dans l’Association Internationale de Pédagogie Expérimentale de langue Française section Canadienne (Dir.), Les modèles en éducation (p. 3-11). Montréal : Édition Noir sur Blanc. Nacro, A. (2000). Réalisation d’un système d’apprentissage générique et adaptable basé sur le Web. Mémoire de maîtrise inédit, Université du Québec à Montréal. Norman, D. A. (1983). Some observations on mental models. Dans D. Gentner et L. A. Stevens (Dirs.), Mental models (p. 7-14). Hillsdale, New Jersey : Lawrence Erlbaum Associates. Norman, D. A. (1986). Cognitive engineering. Dans D. A. Norman et S. W. Draper (Dirs.), User Centered System Design : New Perspectives on Human-Computer Interaction (p. 31-65). Hillsdale, New Jersey : Lawrence Erlbaum Associates. Pacurar E. G., Trigano P. et Alupoaie S. (2005). A QTI editor integrated into the netUniversité web portal using IMS LD. Dans C. Tattersall et R. Koper (Dirs.) Journal of Interactive Media in Education: Advances in Learning Design Special Issue (septembre 2005) [En ligne]. Accès : http://www-jime.open.ac.uk/2005/09/ Petit, Y. (2006). Comparaison entre l’enseignement présentiel et l’enseignement virtuel pour l’apprentissage de l’accord des mots « tout » et « même ». Mémoire de maîtrise inédit, Université du Québec à Montréal. Ponmelil, V.A. (2008). Site Internet corporatif d’ « Education in India » [en ligne]. Accès : http://education.newkerala.com/india-education/Online-Education.html Raby, C. (2007). L’apprentissage par projets. Dans C. Raby et S. Viola (Dirs.), Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie (p. 40-66). Montréal : Les Éditions CEC inc. Raby, C. et Viola, S. (2007). Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie. Dans C. Raby et S. Viola (Dirs.), Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie. Montréal : Les Éditions CEC inc. Richey, R. C. et Nelson, W. A. (1996). Development Research. Dans D. H. Jonassen (Dir.), Handbook of research for educational communications and technology (p. 1213-1245). New-York :Mac Millan. RIDE (2008). Statewide Curriculum [en ligne]. Accès : http://www.ride.ri.gov/Instruction/curriculum/rhodeisland/assessment/tasks.htm Rudestam, K.E. et Schoenholtz-Read J. (2002). The Coming of Age of Adult Online Education. Dans Rudestam, K.E. et Schoenholtz-Read J. (Dirs). Handbook of Online Learning. Thoussand Oaks : Sage Publications. Shneiderman, B. (1992). Designing the User Interface: Strategies for effective HumanComputer Interaction. (2è ed.). New York: Addison-Wesley Publishing Company. SOAP. Simple Object Access Protocol (SOAP) (2009). Accès: http://www.w3.org/TR/soap/ Sodoke, K. (2007). Les normes d’apprentissage à distance. Document inédit, Département d’éducation, Université du Québec à Montréal. Sodoke, K., Nkambou, R., Raîche, G., Riopel, M. et Lesage, M. (2007). Extending Moodle functionnalities to adaptive testing framework. E-Learn 2007, 476-482.

18

Théorêt, M. (2007). Enseignement direct. Dans C. Raby et S. Viola (Dirs.), Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie (p. 208-219). Montréal : Les Éditions CEC Inc. Thinès, G. et L’Empereur, A. (1984). Dictionnaire général des sciences humaines. Louvainla-Neuve : CIACO Éditeur. Van der Maren, J.M. (1996). Méthodes de recherche pour l’éducation : Méthodes en sciences humaines (2ième Édition). Bruxelles : De Boeck. Van der Maren, J.M. (2003). La recherche appliquée en pédagogie : Des modèles pour l’enseignement (2ième Édition). Bruxelles : De Boeck. Van der Veer, G. C., Green, T. R. G., Hoc, J. M. Et Murray, D. M. (1988). Introduction. Dans G. C. Van der Veer, T. R. G. Green, J. M. Hoc et D. M. Murray (Dirs.). Working with computers : Theory versus Outcome (p. xi – xviii). San-Diego : Academic Press. Viola, S. (2007). Enseignements et apprentissages stratégiques. Dans C. Raby et S. Viola (Dirs.), Modèles d’enseignement et théories d’apprentissage : De la pratique à la théorie (p. 135-155). Montréal : Les Éditions CEC Inc. Wahlster, W. (1991). User and discourse models for multimodal communication. Dans J. W. Sullivan et S. W. Tyler (Dirs), Intelligent user interfaces (p. 45 – 67). New-York : ACM Press (Addison-Wesley Publishing Company). XML (2007). Extensible Markup Language. [En ligne] Accès: http://www.w3.org/XML/ XUL (2008). XML User interface Language (XUL). [En ligne] Accès: http://www.mozilla.org/projects/xul/