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Advances in E-learning-Experiences and Methodologies

Formative

Formative Online Assessment in E-Learning formative assessment design. However, he noted that this strategy should be implemented in conjunction with the functions of “provide with no answer” (pushing them to make clear what they did not understand) andinstant feedback,” so that the Web-based formative assessment is more beneficial. For such feedback to be effective it needs to be provided early in the learning process (Brown & Knight, 1994) and to offer guidance for improving performance (William & Black, 1996, p. 543). In the study by Wang, Wang, Wang, and Huang (2006), performance in the multiplechoice Web-based formative assessment group with six strategies, was significantly better than those in both the partial Web-based formative assessment strategy group and the Paper and Pencil Test group. This finding suggests that the more the different formative assessment strategies incorporated in the e-learning environment, the greater the learning effect obtained by students. The Web-based formative assessment condition contained six strategies: 1. “Repeat the test”: This strategy allows students to take the same test item repeatedly if they make errors on it. However, if they pass one test item correctly three times, then the item will be deleted automatically. 2. “Provide with no answer”: This strategy shows students incorrect answers they made without offering the correct answer. However, it also allows students leave the module to find correct answers in their own way. 3. “Ask questions”: This strategy allows students to send questions to the teacher by e-mail. 4. “Query scores”: This strategy provides an interface for students to make queries about peer and personal scores. 5. “Monitor answering history”: This strategy provides an interface for students to check their personal answer history for each item. 6. “All pass and then reward”: This strategy rewards students with a Flash animation when they pass all the test items. desIgn oF ActIvItIes For FormAtIve onLIne Assessment The factors that influence the choice and design of online assessment methods include the learners’ needs, their access to technology, the available resources and, to some extent, the discipline or industry area. Currently, technology offers many new opportunities for innovation in educational assessment through rich new assessment tasks and potentially powerful scoring, reporting, and real-time feedback mechanisms. Through these and other technological innovations, the computer-based platform offers the potential for high quality formative assessment that can closely match instructional activities and goals, and make meaningful contributions to e-learning or summative tests. It is important to examine what is to be learned and assessed, in order to identify appropriate methods for demonstrating these skills. A potential limitation of computer-based assessment resides in the design of questions and tasks with which computers can effectively interact, including scoring and score reporting. recommendations for creating an online Assessment tool Davis and Morrow (2004) suggest five questions for creating an assessment tool: 1. What is it we want to measure? We need to broadly define what it is we want to measure. Specifically, we need to identify the construct of interest. Most often, the topic of interest will fall into one of two categories:

Formative Online Assessment in E-Learning • A type of cognitive achievement, either a knowledge or skill (e.g., maths skills or knowledge of Spanish history). • A type of affective trait (e.g., motivation, interest in maths). The concept of achievement can be broken down into knowledge and skills. Tests of knowledge measure an individual’s understanding and comprehension of facts, concepts, and principles. Tests of skills involve testing the application of this knowledge to problems or situations (Haladyna, 1997). An example of this distinction would be: • Knowledge item: “What is the difference between a median and a mean?” • Skill item: “Given the set of test scores of 55, 89, 74, 68, 92, 73, 85, and 66, compute the mean.” 2. Why are we developing an instrument? There are several reasons why instruments measuring achievement are created: • To assess learning from a particular course or subject area. • To assess the effectiveness or outcome of a program. • To assess level of student knowledge in relation to a particular competence. In addition, the primary reason for the development of an instrument may be its use as a tool for formative assessment. It is important to define the instrument’s purpose in order to justify the time and effort that will be put into the process. 3. How do we want to measure this construct? The commonest type of instrument is a selected response format. This format is relatively easy to administer and easy to score. Despite the benefits of the selected response format, many researchers are exploring the option of performance assessment. Some common examples of performance assessments include having students responding to an essay prompt, playing a piece of music on an instrument, or performing a science experiment in front of a group of raters. The use of computers in test administration has led to the development of adaptive tests, as well as alternative item types with audio or video files, or items that allow for Internet searches. 4. Who will be taking the test? Defining the target population of a test is extremely important at the outset of instrument development, and for several reasons. If a test is made available for public use, the intended set of respondents must be identified. Just as you would not give medicine for an adult to a young child, it is wrong to give a test designed for one population to members of another. Examples of welldefined populations would be: • An assessment of Spanish history knowledge designed for college students. • An assessment of self-confidence for highschool seniors. 5. What are the conditions of measurement? We need to describe how the test will be used. It is important to consider the time and effort involved in developing and scoring the test. With online testing there arise other problems, such as security, cheating, time limits and examinee anxiety. Thus, it is essential to emphasize the need to use a range of methods for collecting evidence of valid assessment. type of Questions and tasks for e-Learning Assessment Formative assessment refers to those activities that are used to help students learn. These types of activities include short tests and quizzes, question, and answers in the lesson, assignments, homework, and so on. Questions, tasks, activities, and other methods of eliciting student responses are often called “items” in the assessment process. One organizational scheme describes innovative

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    Advances in E-Learning: Experiences

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    Table of Contents Preface .........

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    Chapter XIV Open Source LMS Customi

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    Chapter III Philosophical and Epist

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    of constructive and cooperative met

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    Chapter XIV Open Source LMS Customi

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    contents, learning contexts, proces

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    xv these organizations do not get a

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    xvii QuALIty In e-LeArnIng Before t

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    allow that the teachers in training

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    xxi ISO. (1986). Quality-Vocabulary

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    Chapter I RAPAD: A Reflective and P

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    RAPAD in fields such as law, engine

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    RAPAD mystery to the new student. B

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    RAPAD example, whereas Laurillard h

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    RAPAD Ontologically, systems philos

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    RAPAD information related processes

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    RAPAD methods and techniques accord

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    RAPAD 2. An introduction to learnin

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    RAPAD then asked to reflect on and

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    RAPAD Figure 4. A rich picture to h

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    RAPAD Again using techniques from t

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    RAPAD university preparation course

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    RAPAD The third interface is at the

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    RAPAD Knight, P.T., & Trowler, P. (

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    RAPAD AddItIonAL reAdIngs Goodyear,

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    A Heideggerian View on E-Learning t

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    A Heideggerian View on E-Learning (

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    A Heideggerian View on E-Learning s

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    A Heideggerian View on E-Learning r

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    A Heideggerian View on E-Learning o

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    A Heideggerian View on E-Learning n

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    A Heideggerian View on E-Learning M

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    A Heideggerian View on E-Learning W

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Chapter IV E-Mentoring: An Extended

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    E-Mentoring However, what is unders

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    E-Mentoring baugh, & Williams, 2004

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    E-Mentoring Table 2. Contact. Diffe

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    E-Mentoring Table 10. Ethical impli

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    E-Mentoring Table 15. Technology st

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    E-Mentoring Table 21. Coaching. Bes

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    E-Mentoring Table 27. Moment. Best

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    E-Mentoring Moreover, existing rese

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    E-Mentoring Kasprisin, C. A., Singl

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    E-Mentoring Ensher, E. A., Heun, C.

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    Chapter V Training Teachers for E-L

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    Training Teachers for E-Learning FL

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    Training Teachers for E-Learning ne

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    Training Teachers for E-Learning A

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    Training Teachers for E-Learning yo

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    Training Teachers for E-Learning Di

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    Training Teachers for E-Learning ht

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Chapter IX AI Techniques for Monito

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    Chapter X Knowledge Discovery from

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Chapter XI Swarm-Based Techniques i

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Chapter XII E-Learning 2.0: The Lea

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    E-Learning 2.0 Table 1. Different s

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    E-Learning 2.0 Figure 1. Difference

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    E-Learning 2.0 where the blog is al

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    E-Learning 2.0 process. Along this

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    E-Learning 2.0 forth, and, of cours

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    E-Learning 2.0 Finally, it is impor

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    E-Learning 2.0 never be a hotchpotc

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    E-Learning 2.0 McPherson, K. (2006)

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    E-Learning 2.0 Rosen, A. (2006). Te

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    Telematic Environments and Competit

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    E-QUAL 2004; Scalan, 2003) and qual

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    E-QUAL benchmarks address technolog

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    E-QUAL E-learning added two differe

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    E-QUAL Table 6. Application of the

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    E-QUAL Future trends The future of

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    E-QUAL (EQO) co-located to the 4 th

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    E-QUAL SMEs: An analysis of e-learn

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    E-QUAL Meyer, K. A. (2002). Quality

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    Compilation of References Argyris,

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    Compilation of References Biggs, J.

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    Compilation of References Cabero, J

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    Compilation of References Comezaña

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    Compilation of References Downes, S

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    Compilation of References Fandos, M

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    Compilation of References national

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    Compilation of References Hudson, B

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    Compilation of References Harbour.

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    Compilation of References Little, J

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    Compilation of References Metros, S

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    Compilation of References ONeill, K

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    Compilation of References Preece, J

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    Compilation of References Sadler, D

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    Compilation of References Shin, N.,

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    Compilation of References tional Co

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    Compilation of References Vermetten

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    Compilation of References Yu, F. Y.

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    About the Contributors Juan Pablo d

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    About the Contributors part: “An

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    About the Contributors María D. R-

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    About the Contributors Applications

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    Index e-learning tools, automated p

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    Socrates 55 Sophists 55 student-foc

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