EFEKTIVITAS MODEL CIRC DAN TTW BERBANTUAN TEKS DALAM PEMBELAJARAN MENULIS TEKS NONFIKSI SISWA KELAS V SEKOLAH DASAR

ABSTRAK Penelitian ini dilatarbelakangi oleh rendahnya kemampuan siswa menulis teks nonfiksi di kelas V. Penelitian ini bertujuan untuk menguji keefektivan model pembelajaran CIRC berbantuan teks dan model pembelajaran TTW berbantuan teks dalam pembelajaran menulis teks nonfiksi siswa kelas V. Dalam penelitian ini digunakan pendekatan kuantitatif dengan metode kuasi eksperimen. Desain penelitian menggunakan Nonequivalent Control Grup Desain (NCGD). Sampel penelitian ini adalah siswa kelas V A dan kelas V B SDN Situraja, kelas V A sebagai kelas eksperimen yang berjumlah 34 siswa yang terdiri atas 19 laki-laki dan 15 perempuan, kelas V B sebagai kelas kontrol yang berjumlah 35 siswa yang terdiri atas 14 orang laki-laki dan 21 orang perempuan. Instrumen yang digunakan dalam penelitian ini adalah tes. Tes dilakukan dalam dua tahap yaitu prates sebelum diberikan perlakuan dan pascates setelah perlakuan. Analisis data dalam penelitian ini diolah dengan menggunakan bantuan software MS Excel 2010 dan Software IBM SPSS Statistics 23 for Windows. Hasil penelitian menunjukkan bahwa model CIRC berbantuan teks lebih efektif meningkatkan keterampilan menulis teks nonfiksi dibandingkan dengan model TTW berbantuan teks. Hal ini dibuktikan dari nilai signifikansi n-gain yang lebih besar terutama pada indikator isi gagasan yang dikemukakan, organisasi isi, gaya bahasa, gaya pilihan dan struktur kosa kata, ejaan dan tata tulis, kerapihan dan kebersihan tulisan dibandingkan dengan model TTW. Artinya siswa memiliki keterampilan menulis teks nonfiksi lebih baik dengan diajarkanya menggunakan model CIRC berbantuan teks, karena dengan CIRC siswa dituntut untuk bekerjasama dengan teman kelompoknya untuk memahami isi teks nonfiksi serta menuliskan kembali teks nonfiksi sesuai dengan pengalamannya masing-masing. Kata Kunci: Cooperative Integrated Reading and Composition, Think Talk Write, berbantuan teks, menulis, nonfiksi. ABSTRAC This research is motivated by the low ability of students to write non-fiction text in class V. This study aims to examine the effectiveness of the text-assisted CIRC learning model and the text-assisted TTW learning model in learning to write non-fiction text of class V students. In this study a quantitative approach was use. quasi-experimental method. The study design uses the Nonequivalent Control Design Group (NCGD). The sample of this study were VA class students and VB class at SDN Situraja, VA class as an experimental class with 34 students consisting of 19 men and 15 women, VB class as a control class with 35 students consisting of 14 men and 21 women. The instruments used in this study were tests. The test was carried out in two stages, namely pre test before being given treatment and post test after treatment. Data analysis in this study was processed using the help of MS Excel 2010 software and IBM SPSS Statistics 23 for Windows software. The results showed that the CIRC model was more effective in improving the skills of writing non-fiction text compared to the TTW model. This is evidenced from the significance value of n-gain which is greater, especially on the indicator content of the ideas expressed, content organization, language style, choice style and vocabulary structure, spelling and writing, neatness and cleanliness of the writing compared to the TTW model. This means that students have better non-fiction text writing skills taught using the CIRC-assisted text model, because with CIRC students are required to collaborate with their group friends to understand the contents of non-fiction text and rewrite non-fiction text in accordance with their respective experiences. Keywords: Cooperative Integrated Reading and Composition, Think Talk Write, assisted text, writing, non-fiction

Writing In and Around Video Games

This undergraduate course uses video games as a lens through which to explore the infinitely broader topic of digital rhetoric. Students encounter games in several different ways: as texts to analyze, raw material for video compositions, systems to create and explore. Key topics include genre conventions and constraints, audience, procedural rhetoric, interface design, and convergence culture

Development of multiple media documents

Development of documents in multiple media involves activities in three different fields, the technical, the discoursive and the procedural. The major development problems of artifact complexity, cognitive processes, design basis and working context are located where these fields overlap. Pending the emergence of a unified approach to design, any method must allow for development at the three levels of discourse structure, media disposition and composition, and presentation. Related work concerned with generalised discourse structures, structured documents, production methods for existing multiple media artifacts, and hypertext design offer some partial forms of assistance at different levels. Desirable characteristics of a multimedia design method will include three phases of production, a variety of possible actions with media elements, an underlying discoursive structure, and explicit comparates for review

The ModelCC Model-Driven Parser Generator

Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.Comment: In Proceedings PROLE 2014, arXiv:1501.0169

Playing with Play: Machinima in the Classroom

“So, machinima is really a genre, and not a medium?” The students in my Digital Media and Rhetoric course are grappling with both how to define machinima and how to evaluate whether one is “good” or not. I frustrate them by refusing to provide a definitive answer to this and other similar questions they have asked about the form. This intentional frustration continues as, after watching a few examples they ask me what grade I would give those machinima, if they were turned in for this assignment. Rather than providing a simple answer I redirect, asking them what criteria they would use to evaluate machinima and how the examples we’ve seen in class stand up to this scrutiny. At the beginning of this particular unit, when I announced that we wouldn’t be writing another research paper, they were exuberant. Now, however, the complexity of the task before them is slowly unveiling itself. While a majority of these students are gamers, few of them have experience in video production. None of them have previously looked at fan culture as a source of meaning and knowledge production. We are in unfamiliar territory, and they are getting restless

The computer as means of communication for peer-review groups

In a scientific-writing course, 15 of 54 students used a review-supporting computer program, PREP-EDITOR (PREP), to communicate with their peers about drafts. In an exploratory study, 10 students were interviewed regularly: 5 used PREP and 5 met face-to-face to exchange comments on drafts. The study showed that use of PREP did not increase time spent on various writing activities. The PREP group reported a large number of computer-related problems, whereas the non-PREP group reported more difficulties with assignments and course organization. It appeared that the technology was omnipresent in PREP users' perception of the course. The system of computer-mediated peer review has many of the drawbacks of 'distance learning,' but because networks are increasingly used by collaborating authors, we should teach our students how to use them sensibly

NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings

Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we argue that effort to developing service descriptions, request translations, and matching mechanisms could be reduced using unrestricted natural language; allowing both: (1) end-users to intuitively express their needs using natural language, and (2) service developers to develop services without relying on syntactic/semantic description languages. Although there are some natural language-based service composition approaches, they restrict service retrieval to syntactic/semantic matching. With recent developments in Machine learning and Natural Language Processing, we motivate the use of Sentence Embeddings by leveraging richer semantic representations of sentences for service description, matching and retrieval. Experimental results show that service composition development effort may be reduced by more than 44\% while keeping a high precision/recall when matching high-level user requests with low-level service method invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on Services Computing) on July 1