COMPUTER PROGRAMMING IN C LECTURE NOTES

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A textbook of Computer Based Numerical and Statiscal Techniques part 57 pps

A TEXTBOOK OF COMPUTER BASED NUMERICAL AND STATISCAL TECHNIQUES PART 57 PPS

At its most basic level, programming a computer simply means telling it what to do, and thisvapid-sounding definition is not even a joke. There are no other truly fundamental aspects ofcomputer programming; everything else we talk about will simply be the details of a particular[r]

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Lecture Notes in Computer Science- P28 pps

LECTURE NOTES IN COMPUTER SCIENCE P28 PPS

for reasons of readability. In fact, in each type of stage only some types of activities are allowed. For example, constructing QTI items/test and designing demonstration assignment can only been specified in the design stage. In the evidence collection stage only respond[r]

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Lecture Notes in Computer Science- P26 pptx

LECTURE NOTES IN COMPUTER SCIENCE P26 PPTX

Fig. 2. Case Development of “2002-2004 Lack of electricity all over China” Section 1 Case Selection and grouping. In this section, students initially read pub-lished cases and recommended resources in WebCASE case database, then selecting cases, grouping and voting for group leaders. S[r]

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Lecture Notes in Computer Science- P27 pot

LECTURE NOTES IN COMPUTER SCIENCE P27 POT

120 X. Zhang, N. Luo, and L. Zheng To reveal the objectivity and veracity, current study research and evaluation often use rubric evaluation methods. In case study of course “Industry System Introduction” in 2007 spring semester, we design case study evaluation rubric to evaluate stude[r]

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Lecture Notes in Computer Science- P29 docx

LECTURE NOTES IN COMPUTER SCIENCE P29 DOCX

140 Y. Miao, P. Sloep, and R. Koper 4 An Initial Validation of the Conceptual Model Validation studies have been conducted to test if the conceptual model would meet the requirements described in section 2. In this section, we present the results of these initial validation studies. Co[r]

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Lecture Notes in Computer Science- P30 pps

LECTURE NOTES IN COMPUTER SCIENCE P30 PPS

F. Li et al. (Eds.): ICWL 2008, LNCS 5145, pp. 132–144, 2008. © Springer-Verlag Berlin Heidelberg 2008 Modeling Units of Assessment for Sharing Assessment Process Information: Towards an Assessment Process Specification Yongwu Miao, Peter Sloep, and Rob Koper Educational Technology Expertise Center,[r]

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Lecture Notes in Computer Science- P31 pps

LECTURE NOTES IN COMPUTER SCIENCE P31 PPS

Modeling Units of Assessment for Sharing Assessment Process Information 137 Each choice will provide additional restrictions to the conceptual model. For example, in a peer assessment many concepts will be excluded. A detailed example of a peer assessment is given in [19]. Role is used[r]

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Lecture Notes in Computer Science- P23 potx

LECTURE NOTES IN COMPUTER SCIENCE- P23 POTX

cluding their diverse functionalities into usable and effective e/mLearning environ-ment [23]: (i) an eLearning portal, supporting the learning process and specifically, 102 C. Hornung et al. group-oriented learning in classes of pupils, (ii) an eKnowledge repository, containing tradit[r]

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Lecture Notes in Computer Science- P21 pot

LECTURE NOTES IN COMPUTER SCIENCE P21 POT

32% of schools in Taiwan already took part in the PBL.NET project. The number of WebQuest lessons submitted by teachers is also an indication of significance. As of 92 Y T. Carolyn Yang et al. October 2007, over 2000 WebQuest lessons were shared in the “Digital Library.” The wea[r]

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Lecture Notes in Computer Science- P22 pdf

LECTURE NOTES IN COMPUTER SCIENCE P22 PDF

The Practice and Experience Sharing of Three-Year Peer Coaching Program in Taiwan 95 all significantly higher than those on their posttests, t=3.48, p=.00, t=2.80, p=.01, and t=2.50, p=.02, respectively; for coaches, t=5.31, p=.00, t=5.47, p=.00, and t=5.10, p=.00, respectively. These results[r]

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Lecture Notes in Computer Science- P24 ppsx

LECTURE NOTES IN COMPUTER SCIENCE P24 PPSX

eKnowledge Repositories in eLearning 2.0 105 elements; different course elements can be distinguished by different colors. A meta-data search engine is integrated, so that content can be searched for during the course creation process. Fig. 3 shows screenshots from different graphical element[r]

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Lecture Notes in Computer Science- P25 docx

LECTURE NOTES IN COMPUTER SCIENCE P25 DOCX

110 C. Hornung et al. 16. Garris, R., Ahlers, R., Driskell, J.E.: Games, Motivation and Learning: Research and Prac-tice Model. Simulation & Gaming. Sage Publications, Newsbury Park (2002) 17. Butler, D.L., Winne, P.H.: Feedback and Self-Regulated Learning: A Theoretical Synthe-sis. R[r]

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Lecture Notes in Computer Science- P38 pps

LECTURE NOTES IN COMPUTER SCIENCE P38 PPS

documentation, tutorship, communication tools, etc. However, the students have also highlighted some negative aspects, like an excess of competitiveness and an increase of work volume. The teachers also have reported an when students dare to submit their own challenges In this sense, QUESTour[r]

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Lecture Notes in Computer Science- P36 pot

LECTURE NOTES IN COMPUTER SCIENCE- P36 POT

Meaning (Item Group) 32.04% (502) 20.49% (321) 37.97% (595) 9.51% (149) 100% (1567) Table 4. Distribution of Items in Bloom's Taxonomy by CAGIS Cognitive Process Dimension Knowledge Dimensions Remember Understand Apply Analyze Evaluate Total Factual 555 (35.42%) 0 (0%) 245(15.63%) 0 (0%) 809([r]

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Lecture Notes in Computer Science- P37 pptx

LECTURE NOTES IN COMPUTER SCIENCE P37 PPTX

Motivating Students through On-Line Competition 169 In another line, Kim and Sonnenwald [12] use the scale of learning preferences of Owens and Barnes to identify three learning styles: cooperative, competitive and individualized. The cooperative learning style indicates a preference for achi[r]

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Lecture Notes in Computer Science- P39 doc

LECTURE NOTES IN COMPUTER SCIENCE P39 DOC

Collaborative Learning Tool Applying to C Programming Language 179 the effectiveness of collaborative learning [4, 5 and 6]. During the collaborative learn-ing process, all teammates will benefit from each other [7]. The approach to education that is more suitable to the educational en[r]

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Lecture Notes in Computer Science- P40 pptx

LECTURE NOTES IN COMPUTER SCIENCE P40 PPTX

184 W C. Chang and K C. Chen share files with other members within a conversation. Files are shared using the Shared Files collaboration channel visible within each conversation window. Our tool has some elements that are differ from the above-mentioned tool. Now, we will address some[r]

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Lecture Notes in Computer Science- P33 pot

LECTURE NOTES IN COMPUTER SCIENCE P33 POT

tion” and “Multimedia Attachment”. ¾ Knowledge of specific details and elements: major natural resources and reliable sources of information. In Fig. 1, such type of knowledge is stored through “Description”, “Property”, “Instance”, “Holonymy”, “Meronymy”, “Near Synonymy”, “Synonymy”, and “An[r]

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Lecture Notes in Computer Science- P32 pps

LECTURE NOTES IN COMPUTER SCIENCE P32 PPS

142 Y. Miao, P. Sloep, and R. Koper concept support-activity in LD. An assessment process model based on APS can be transformed into an executable model represented in LD and QTI. Thus, we should be able to use an integrated LD and QTI run-time environment to execute various forms of a[r]

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Lecture Notes in Computer Science- P35 ppt

LECTURE NOTES IN COMPUTER SCIENCE P35 PPT

ScoringParameterHomonym Analysis ParameterConcept NumberItemNumberItemScoreMaterial Mapping FeedbackKnowledgeDimensionCognitiveDimensionItem Structure OntologyVariable Item Structure Variable ItemOperands Variable Item Original Item Multiple Response Fig. 2. Test Item Structure Ontology 2.4 CAGIS Sy[r]

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