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STATUS PERTANIKA JSSH MENURUT SJR – TANGGAL 24 APRIL 2018 DITELUSURI MELALUI URL: http://www.scimagojr.com/journalsearch.php?q=19600162021&tip=sid&clean=0 Lampiran C-2

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STATUS PERTANIKA JSSH MENURUT SJR – TANGGAL 24 APRIL 2018DITELUSURI MELALUI URL: http://www.scimagojr.com/journalsearch.php?q=19600162021&tip=sid&clean=0

Lampiran C-2

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Status Kuartil: Q2

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VOL. 25 (S) SEPT. 2017

Vol. 25 (S) Sept 2017

Pertanika Editorial O�ce, Journal DivisionO�ce of the Deputy Vice Chancellor (R&I) 1st Floor, IDEA Tower II UPM-MTDC Technology CentreUniversiti Putra Malaysia43400 UPM SerdangSelangor Darul EhsanMalaysia

http://www.pertanika.upm.edu.my/E-mail: [email protected]: +603 8947 1622

A special edition devoted toIssues in IT and Innovation of Teacher Training Education

Guest EditorsMurni Ramli, Indah Widiastuti & Nur Arifah Drajati

http://penerbit.upm.edu.my

Pertanika Journal of Social Sciences & Humanities Vol. 25 (S) SEPT. 2017

Contents

Issues in IT and Innovation of Teacher Training Education ngieroF a sa hsilgnE etavitcA ot gninraeL dednelB :elcitrA weiveR

Language (EFL) Learners’ Autonomy 1

Lusiana Prihastiwi, Dewi Rochsantiningsih and Suparno

Review Article: Massively Multiplayer Online Role Playing Game (MMORPG): An Alternative Medium in English Language Teaching (ELT)

11

Mohammad Romdhoni Prakoso, Ngadiso and Sumardi

Literacy Practices of Vocational Engineering Pre-Teachers in Surveying and Mapping

25

Anis Rahmawati

Development of the Science Skills of Lower Secondary Students in a Chemistry Laboratory Experiment

41

Budi Utami, Sulistyo Saputro, Ashadi, Mohammad Masykuri, Sri Yamtinah and Sri Widoretno

Practices of Inquiry-based Science Education: Case Study of Thailand’s Junior High School

51

Citra Mashita, Murni Ramli and Puguh Karyanto

Introducing Indigenous Culture into Online-based Courses 73Cucuk Wawan Budiyanto, Indah Widiastuti and Endar S. Wihidayat

evitaerC ni ecnamrofreP lairuenerpertnE eht esaercnI ot ledoM ehTIndustries Using Entrepreneurial Orientation and Social Capital Development Approach

85

Dewi Kusuma Wardani, Feri Setyowibowo, Muhammad Sabandi and Leny Noviani

Showing “Respect” in a Multicultural Society in Central Sulawesi: A Sociopragmatics Study of Directive Speech Acts in a Local Language in a University Academic Environment

99

Fatma, Sumarlam, Sarwiji Suwandi and Ani Rakhmawati

Students115

Imam Sujadi and Ulfa Masamah

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Journal of Social Sciences & Humanities

About the JournalOverviewPertanika Journal of Social Sciences & Humanities (JSSH) is the official journal of Universiti Putra Malaysia published by UPM Press. It is an open-access online scientific journal which is free of charge. It publishes the scientific outputs. It neither accepts nor commissions third party content.

Recognized internationally as the leading peer-reviewed interdisciplinary journal devoted to the publication of original papers, it serves as a forum for practical approaches to improving quality in issues pertaining to social and behavioural sciences as well as the humanities.

JSSH is a quarterly (March, June, September and December) periodical that considers for publication original articles as per its scope. The journal publishes in English and it is open to authors around the world regardless of the nationality.

The Journal is available world-wide.

Aims and scopePertanika Journal of Social Sciences & Humanities aims to develop as a pioneer journal for the social sciences with a focus on emerging issues pertaining to the social and behavioural sciences as well as the humanities.

Areas relevant to the scope of the journal include Social Sciences—Accounting, anthropology, Archaeology and history, Architecture and habitat, Consumer and family economics, Economics, Education, Finance, Geography, Law, Management studies, Media and communication studies, Political sciences and public policy, Population studies, Psychology, Sociology, Technology management, Tourism; Humanities—Arts and culture, Dance, Historical and civilisation studies, Language and Linguistics, Literature, Music, Philosophy, Religious studies, Sports.

HistoryPertanika was founded in 1978. A decision was made in 1992 to streamline Pertanika into three journals as Journal of Tropical Agricultural Science, Journal of Science & Technology, and Journal of Social Sciences & Humanities to meet the need for specialised journals in areas of study aligned with the interdisciplinary strengths of the university.

After almost 25 years, as an interdisciplinary Journal of Social Sciences & Humanities, the revamped journal focuses on research in social and behavioural sciences as well as the humanities, particularly in the Asia Pacific region.

Goal of PertanikaOur goal is to bring the highest quality research to the widest possible audience.

Quality We aim for excellence, sustained by a responsible and professional approach to journal publishing. Submissions are guaranteed to receive a decision within 14 weeks. The elapsed time from submission to publication for the articles averages 5-6 months.

Abstracting and indexing of PertanikaPertanika is almost 40 years old; this accumulated knowledge has resulted in Pertanika JSSH being abstracted and indexed in SCOPUS (Elsevier), Thomson (ISI) Web of Science™ Core Collection Emerging Sources Citation Index (ESCI). Web of Knowledge [BIOSIS & CAB Abstracts], EBSCO and EBSCOhost, DOAJ, Google Scholar, TIB, MyCite, ISC, Cabell’s Directories & Journal Guide.

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Future visionWe are continuously improving access to our journal archives, content, and research services. We have the drive to realise exciting new horizons that will benefit not only the academic community, but society itself.

Citing journal articlesThe abbreviation for Pertanika Journal of Social Sciences & Humanities is Pertanika J. Soc. Sci. Hum.

Publication policyPertanika policy prohibits an author from submitting the same manuscript for concurrent consideration by two or more publications. It prohibits as well publication of any manuscript that has already been published either in whole or substantial part elsewhere. It also does not permit publication of manuscript that has been published in full in Proceedings.

Code of EthicsThe Pertanika Journals and Universiti Putra Malaysia takes seriously the responsibility of all of its journal publications to reflect the highest in publication ethics. Thus all journals and journal editors are expected to abide by the Journal’s codes of ethics. Refer to Pertanika’s Code of Ethics for full details, or visit the Journal’s web link at http://www.pertanika.upm.edu.my/code_of_ethics.php

International Standard Serial Number (ISSN)An ISSN is an 8-digit code used to identify periodicals such as journals of all kinds and on all media–print and electronic. All Pertanika journals have ISSN as well as an e-ISSN.

Journal of Social Sciences & Humanities: ISSN 0128-7702 (Print); ISSN 2231-8534 (Online).

Lag time A decision on acceptance or rejection of a manuscript is reached in 3 to 4 months (average 14 weeks). The elapsed time from submission to publication for the articles averages 5-6 months.

AuthorshipAuthors are not permitted to add or remove any names from the authorship provided at the time of initial submission without the consent of the Journal’s Chief Executive Editor.

Manuscript preparationRefer to Pertanika’s Instructions to Authors at the back of this journal.

Most scientific papers are prepared according to a format called IMRAD. The term represents the first letters of the words Introduction, Materials and Methods, Results, And, Discussion. IMRAD is simply a more ‘defined’ version of the “IBC” [Introduction, Body, Conclusion] format used for all academic writing. IMRAD indicates a pattern or format rather than a complete list of headings or components of research papers; the missing parts of a paper are: Title, Authors, Keywords, Abstract, Conclusions, and References. Additionally, some papers include Acknowledgments and Appendices.

The Introduction explains the scope and objective of the study in the light of current knowledge on the subject; the Materials and Methods describes how the study was conducted; the Results section reports what was found in the study; and the Discussion section explains meaning and significance of the results and provides suggestions for future directions of research. The manuscript must be prepared according to the Journal’s Instructions to Authors.

Editorial processAuthors are notified with an acknowledgement containing a Manuscript ID on receipt of a manuscript, and upon the editorial decision regarding publication.

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Pertanika follows a double-blind peer-review process. Manuscripts deemed suitable for publication are usually sent to reviewers. Authors are encouraged to suggest names of at least three potential reviewers at the time of submission of their manuscript to Pertanika, but the editors will make the final choice. The editors are not, however, bound by these suggestions.

Notification of the editorial decision is usually provided within ten to fourteen weeks from the receipt of manuscript. Publication of solicited manuscripts is not guaranteed. In most cases, manuscripts are accepted conditionally, pending an author’s revision of the material.

As articles are double-blind reviewed, material that might identify authorship of the paper should be placed only on page 2 as described in the first-4 page format in Pertanika’s Instructions to Authors given at the back of this journal.

The Journal’s peer-reviewIn the peer-review process, three referees independently evaluate the scientific quality of the submitted manuscripts.

Peer reviewers are experts chosen by journal editors to provide written assessment of the strengths and weaknesses of written research, with the aim of improving the reporting of research and identifying the most appropriate and highest quality material for the journal.

Operating and review processWhat happens to a manuscript once it is submitted to Pertanika? Typically, there are seven steps to the editorial review process:

1. The Journal’s chief executive editor and the editorial board examine the paper to determine whether it is appropriate for the journal and should be reviewed. If not appropriate, the manuscript is rejected outright and the author is informed.

2. The chief executive editor sends the article-identifying information having been removed, to three reviewers. Typically, one of these is from the Journal’s editorial board. Others are specialists in the subject matter represented by the article. The chief executive editor asks them to complete the review in three weeks.

Comments to authors are about the appropriateness and adequacy of the theoretical or conceptual framework, literature review, method, results and discussion, and conclusions. Reviewers often include suggestions for strengthening of the manuscript. Comments to the editor are in the nature of the significance of the work and its potential contribution to the literature.

3. The chief executive editor, in consultation with the editor-in-chief, examines the reviews and decides whether to reject the manuscript, invite the author(s) to revise and resubmit the manuscript, or seek additional reviews. Final acceptance or rejection rests with the Edito-in-Chief, who reserves the right to refuse any material for publication. In rare instances, the manuscript is accepted with almost no revision. Almost without exception, reviewers’ comments (to the author) are forwarded to the author. If a revision is indicated, the editor provides guidelines for attending to the reviewers’ suggestions and perhaps additional advice about revising the manuscript.

4. The authors decide whether and how to address the reviewers’ comments and criticisms and the editor’s concerns. The authors return a revised version of the paper to the chief executive editor along with specific information describing how they have answered’ the concerns of the reviewers and the editor, usually in a tabular form. The author(s) may also submit a rebuttal if there is a need especially when the author disagrees with certain comments provided by reviewer(s).

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5. The chief executive editor sends the revised paper out for re-review. Typically, at least one of the original reviewers will be asked to examine the article.

6. When the reviewers have completed their work, the chief executive editor in consultation with the editorial board and the editor-in-chief examine their comments and decide whether the paper is ready to be published, needs another round of revisions, or should be rejected.

7. If the decision is to accept, an acceptance letter is sent to all the author(s), the paper is sent to the Press. The article should appear in print in approximately three months.

The Publisher ensures that the paper adheres to the correct style (in-text citations, the reference list, and tables are typical areas of concern, clarity, and grammar). The authors are asked to respond to any minor queries by the Publisher. Following these corrections, page proofs are mailed to the corresponding authors for their final approval. At this point, only essential changes are accepted. Finally, the article appears in the pages of the Journal and is posted on-line.

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VOL. 25 (S) SEPT. 2017(Special Edition)

A special edition devoted to Issues in IT and Innovation of Teacher Training Education

A scientific journal published by Universiti Putra Malaysia Press

Guest EditorsMurni Ramli, Indah Widiastuti & Nur Arifah Drajati

SOCIAL SCIENCES & HUMANITIES

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JSSHJournal of Social Sciences & Humanities

AN INTERNATIONAL PEER-REVIEWED JOURNALEDITOR-IN-CHIEFMohd. Shahwahid Hj. OthmanEconomics, Natural Resource & Environmental Economics, Economics Valuation

CHIEF EXECUTIVE EDITORNayan Deep S. Kanwal Environmental Issues – Landscape Plant Modelling Applications

UNIVERSITY PUBLICATIONS COMMITTEEHusaini Omar, Chair

EDITORIAL STAFFJournal Officers:Kanagamalar Silvarajoo, ScholarOne

Tee Syin-Ying, ScholarOneChai Sook Keat, ScholarOneUmmi Fairuz Hanapi, Publication Officer

Editorial Assistants:

Zulinaardawati Kamarudin Florence Jiyom Rahimah Razali

COPY EDITORSDoreen Dillah Crescentia Morais Pooja Terasha Stanslas

PRODUCTION STAFFPre-press Officer:Nur Farrah Dila IsmailKanagamalar SilvarajooWong Lih Jiun

Layout & Typeset:Loh Kian Lin

WEBMASTERMohd Nazri Othman

PUBLICITY & PRESS RELEASEMagdalene Pokar (ResearchSEA) Florence Jiyom

EDITORIAL OFFICEJOURNAL DIVISION Office of the Deputy Vice Chancellor (R&I) 1st Floor, IDEA Tower II UPM-MTDC Technology Centre Universiti Putra Malaysia 43400 Serdang, Selangor Malaysia.Gen Enq.: +603 8947 1622 | 1616E-mail: [email protected]: www.journals-jd.upm.edu.my

PUBLISHERKamariah Mohd SaidinUPM Press Universiti Putra Malaysia 43400 UPM, Serdang, Selangor, Malaysia.Tel: +603 8946 8855, 8946 8854 Fax: +603 8941 6172

EDITORIAL BOARD2015-2017Abdul Mansur M. MasihEconomics, Econometrics, Finance, King Fahd University of Petroleum and Minerals, Saudi Arabia.

Alan Maley English Language Studies, Teaching of English Language and Literature, Leeds Metropolitan University, UK.

Ali Reza Kaldi Medical Sociology, Sociology of Development Ageing, Gerontology, University of Social Welfare and Rehabilitation, Tehran, Iran.

Aminah Ahmad Sociology, Gender and Development, Universiti Putra Malaysia, Malaysia.

Bee-Hoon Tan Faculty of Social Sciences and Liberal Arts, UCSI University, Malaysia.

Brian Tomlinson English Language Studies, The Evaluation, Adaptation and Development, Leeds Metropolitan University, UK.

Deanna L. Sharpe Economics, Consumer and Family Economics, Personal Finance, The University of Missouri, Columbia, USA.

Dessy IrawatiInternational Business Management, Strategic Management, Economic Geography, Globalization and Development Studies, Industrial Dynamics and Knowledge Transfer, Radboud University, the Netherlands and EduPRIME the consulting, the Netherlands.

Elias @ Ilias SallehKuliyyah of Architecture and Environmental Design (KAED), Universiti Islam Antarabangsa Malaysia, Malaysia.

Barbara WejnertPolitical Sociologist: Gender Studies, Macro Political and Social Changes, University at Buffalo, SUNY, USA.

Carolyn GrahamMusic, Jazz Chants, Harvard University, USA.

David NunanVice-President: Academic, Anaheim University, California, English Language Studies, Linguist, TESOL, University of Hong Kong, Hong Kong.

Faith Trent AM FACEEducation: Curriculum development, Flinders University, Adelaide, Australia.

Gary N. McleanExecutive Director, International Human Resource Development Programs, EAHR, Human Resource Development for National, Community and Social Development, International Human Resource Development, Organizational Development, Texas A&M University, USA.

Graham Thurgood English Language Studies, General Linguistics, Discourse and Syntax, California State University, Chico., USA.

Gong-Soog Hong Economics, Consumer and Family Sciences, The Ohio State University, USA.

Jacqueline Pugh-Kitingan Music, Ethnomusicology, Borneo and Papua New Guinea Studies, Universiti Malaysia Sabah, Malaysia.

James R. Stock Management Studies, Marketing, Logistics and Supply Chain Management, Quantitative Method, University of South Florida, USA.

Jayakaran Mukundan English Language Studies, Teaching English as a Second Language (TESL), English Language Studies, Universiti Putra Malaysia, Malaysia.

Jayum A. Jawan Sociology, Politics and Government, Civilization Studies, Universiti Putra Malaysia, Malaysia.

Jonathan Newton Classroom-based Second Language Acquisition, Language Teaching Methodology, the Interface of Culture and Language in Language Teaching and Learning, and Language/Communication Training and Material Design for the Multicultural Workplace, Victoria University of Wellington, New Zealand.

Marcus Bion GRIFFINHuman Ecology, Anthropology, Tropical Agriculture, Fisheries, Cultural Learning Solutions, USA.

Mary Susan PhilipEnglish Language Theatre in Malaysia and Singapore; Postcolonial Theatre, University of Malaya, Malaysia.

Muzafar Shah Habibullah Economics, Monetary Economics, Banking, Macroeconomics, Universiti Putra Malaysia, Malaysia.

Patricia Matusky Music, Ethnomusicology, Malay and Indonesian language, Literature and Culture, Grand Valley State University, USA.

Rohany Nasir Psychology-Career counseling, Counseling for Adolescents and Adults, Marriage and Family counseling, Counseling industry and Organization, Universiti Kebangsaan Malaysia, Malaysia.

Samsinar Md. Sidin Management Studies, Marketing, Consumer Behaviour, Universiti Putra Malaysia, Malaysia.

Shameem Rafik-GaleaEnglish Language Studies, Linguistics, Applied Linguistics, Language and Communication, Universiti Putra Malaysia, Malaysia.

Shamsher Mohamad Ramadili Mohd Finance, Corporate Governance, The Global University of Islamic Finance (INCEIF) Malaysia.

Stephen J. Hall English Language Studies, Linguist, Teacher Educator, TESOL, Sunway University College, Malaysia.

Stephen J. Thoma Phsycology, Educational Psychology, The University of Alabama, USA.

Swee-Heng Chan Malaysia.

Turiman Suandi Psychology, Youth Development and Volunteerism, Universiti Putra Malaysia, Malaysia.

Victor T. King Anthropology / Southeast Asian Studies White Rose East Asia Centre, University of Leeds, UK.

INTERNATIONAL ADVISORY BOARD2017-2019

Handoyo Puji Widodo English Language Center, Shantou University, China.

John R. Schermerhorn Jr. Management Studies, Management and Organizational Behaviour, International Business, Ohio University, USA.

Kent Matthews Economics, Banking and Finance, Modelling and Forecasting the Macro Economy, Cardiff Business School, UK.

Lehman B. Fletcher Economics, Agricultural Development, Policy Analysis and Planning, Iowa State University, USA.

Mark P. Orbe Communication, Interpersonal Communication, Communication and Diversity, Intercultural Communication, Western Michigan University, USA.

Mohamed Ariff Department of Economics and Finance, Sunway University, Malaysia.

Pal Ahluwalia Pro Vice-Chancellor (Research and Innovation), African Studies, Social and Cultural Theory, Post-colonial Theory, Division of Education, Arts & Social Sciences, University of Portsmouth, United Kingdom.

Phillip Jones Architectural Science, Sustainability in the Built Environment, Welsh School of Architecture, Cardiff University, UK.

Rance P. L. Lee Sociology, The Chinese University of Hong Kong.

Royal D. Colle Communication, Cornell University, USA.

Shonda Buchanan Interim Chair, American Literature, Hampton University, USA.

Vijay K. Bhatia Education: Genre Analysis and Professional Communication, City University of Hong Kong

ABSTRACTING/INDEXINGPertanika is now over 40 years old; this accumulated knowledge has resulted the journals being indexed in abstracted in SCOPUS (Elsevier), Thomson (ISI) Web of Knowledge [ESCI, BIOSIS & CAB Abstracts], EBSCO & EBSCOhost, ERA, DOAJ, AGRICOLA (National Agric. Library, USA), Cabell’s Directories, Google Scholar, MyAIS, Islamic World Science Citation Center (ISC), ASEAN Citation Index (ACI) & Rubriq (Journal Guide).

The publisher of Pertanika will not be responsible for the statements made by the authors in any articles published in the journal. Under no circumstances will the publisher of this publication be liable for any loss or damage caused by your reliance on the advice, opinion or information obtained either explicitly or implied through the contents of this publication.All rights of reproduction are reserved in respect of all papers, articles, illustrations, etc., published in Pertanika. Pertanika provides free access to the full text of research articles for anyone, web-wide. It does not charge either its authors or author-institution for refereeing/publishing outgoing articles or user-institution for accessing incoming articles.No material published in Pertanika may be reproduced or stored on microfilm or in electronic, optical or magnetic form without the written authorization of the Publisher.Copyright © 2017-18 Universiti Putra Malaysia Press. All Rights Reserved.

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Preface

The second International Conference on Teacher Training and Education (ICTTE) 2016 invites researchers, academicians, educators, practitioners, government agencies, and consultants around the world to attend and share their insights, perspectives and new trends of research which relate to the theme of the conference, “Strengthening IT and Innovation of Teacher Training Education in the Era of Global Competitiveness.” The conference, was organized by the Faculty of Teacher Training and Education, Universitas Sebelas Maret, was held in Surakarta, Central Java, Indonesia, from 23-24 November 2016.

Each of the full papers submitted to the conference was peer reviewed by at least two reviewers. There were 245 manuscripts submitted to the conference; however, due to Pertanika’s stringent peer-review process, only 24 were selected for publication in this special issue.

Our deepest gratitude goes to Dr. Nayan KANWAL of the Journal Division, and the team of Editorial Office, Pertanika, Universiti Putra Malaysia, for their wisdom and invaluable advice especially during the early stages of our own learning process of ensuring that manuscripts are suitable for journal publication. Through this experience, we have been able to deepen our knowledge of the demanding processes involved in the publication of Pertanika special issues.

Guest Editors:

Murni Ramli (Dr.)Indah Widiastuti (Dr.)Arifah Nur Drajati (Dr.)Khresna Bayu Sangka (Dr.)Cucuk W Budiyanto (Dr.)Nurma Yunita Indriyanti (Dr. paed.)

September 2017

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Pertanika Journal of Social Sciences & Humanities Vol. 25 (S) Sept. 2017

Contents

Issues in IT and Innovation of Teacher Training EducationReview Article: Blended Learning to Activate English as a Foreign Language (EFL) Learners’ Autonomy

1

Lusiana Prihastiwi, Dewi Rochsantiningsih and Suparno

Review Article: Massively Multiplayer Online Role Playing Game (MMORPG): An Alternative Medium in English Language Teaching (ELT)

11

Mohammad Romdhoni Prakoso, Ngadiso and Sumardi

Literacy Practices of Vocational Engineering Pre-Teachers in Surveying and Mapping

25

Anis Rahmawati

Development of the Science Skills of Lower Secondary Students in a Chemistry Laboratory Experiment

41

Budi Utami, Sulistyo Saputro, Ashadi, Mohammad Masykuri, Sri Yamtinah and Sri Widoretno

Practices of Inquiry-based Science Education: Case Study of Thailand’s Junior High School

51

Citra Mashita, Murni Ramli and Puguh Karyanto

Introducing Indigenous Culture into Online-based Courses 73Cucuk Wawan Budiyanto, Indah Widiastuti and Endar S. Wihidayat

The Model to Increase the Entrepreneurial Performance in Creative Industries Using Entrepreneurial Orientation and Social Capital Development Approach

85

Dewi Kusuma Wardani, Feri Setyowibowo, Muhammad Sabandi and Leny Noviani

Showing “Respect” in a Multicultural Society in Central Sulawesi: A Sociopragmatics Study of Directive Speech Acts in a Local Language in a University Academic Environment

99

Fatma, Sumarlam, Sarwiji Suwandi and Ani Rakhmawati

Mathematical Reflective Thinking Processesof Senior High School Students

115

Imam Sujadi and Ulfa Masamah

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Pertanika J. Soc. Sci. & Hum. 25 (S): 153 - 168 (2017)

ISSN: 0128-7702 © Universiti Putra Malaysia Press

SOCIAL SCIENCES & HUMANITIESJournal homepage: http://www.pertanika.upm.edu.my/

E-mail addresses: [email protected] (Joni Rokhmat)[email protected] (Marzuki)[email protected] (Hikmawati)[email protected] (Ni Nyoman Sri Putu Verawati) * Corresponding author

Article history:Received: 01 December 2016Accepted: 23 August 2017

ARTICLE INFO

The Causal Model in Physics Learning with a Causalitic-thinking Approach to Increase the Problem-solving Ability of Pre-service Teachers

Joni Rokhmat1*, Marzuki2, Hikmawati1 and Ni Nyoman Sri Putu Verawati1 1Physics Education Programme, Universitas Mataram, Mataram, Indonesia2Department of Physics, Universitas Mataram, Mataram, Indonesia

ABSTRACT

The causal model is a specific relational pattern for the cause and effect of a phenomenon in learning with a causalitic-thinking approach (CTA) (causalitic means a combination of causality and analytic). This approach is oriented to increasing the problem-solving ability (PSA) of pre-service teachers and has been implemented in two subjects: work and energy, and thermodynamics. PSA includes the ability to understand (IPSA-1), select (IPSA-2), differentiate (IPSA-3), determine (IPSA-4), apply (IPSA-5), and identify (IPSA-6). This research aimed to investigate causal models in learning Physics, which are possible to develop for increasing PSA. This research was conducted by using a mixed method of an embedded, experimental, two phase design and used a sample of 49 students, with 39 females and 10 males. The differences between pre-test and post-test, and between the PSA gain of the low (Lo) and high (Hi) groups were tested using the Wilcoxon signed-ranks test. Results of the test on the subjects, among all pairs (24 pairs) of tcounted and ttable, showed that there are differences of 71% (for pre- and post-test) and 33% (for Lo and Hi groups) that indicated tcounted<ttable. However, from the investigation of the physics phenomena used, there are six causal models as a result of the first year of this series of research. The models are simple causal model (SCM), divergent causal model (DCM), convergent causal model

(CCM), chain causal model (ChCM), simple composite causal model (SCoCM), and chain composite causal model (ChCoCM). These models are useful as references when constructing phenomena for conducting Physics learning or learning for another discipline using this approach.

Keywords: Causal-model, causalitic-thinking

approach, physics-learning, problem-solving ability

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INTRODUCTION

Many researchers have investigated learning strategies to improve the quality of physics learning. Examples of these are the use of conflict-cognitive learning (Baser, 2006); the process of meta-conceptual awareness, meta-conceptual monitoring and meta-conceptual evaluation (Yürük, 2007); interactive engagement (Hake, 2007); theorem-in-action (Escudero, Moreira, & Caballero, 2009); and the use of demonstration of three accelerated movements (Dykstra & Sweet, 2009). Other examples are the use of technology-enabled-active-learning (TEAL) studio format (Dori & Belcher, 2004); Powerpoint presentation and experimental demonstration (Obaidat & Malkawi, 2009); causal reasoning (Hung & Jonassen, 2006), Physics lecturing programme (PLP), which was designed to increase the ability to analyse and create (Rasagama, 2011); and the use of causality and analytical-thinking approach to increase students’ problem-solving ability (PSA) (Rokhmat, 2013).

Rokhmat (2013) investigated the impact of a causalitic learning approach on the PSA for seven subjects: kinematics, Newton’s law of motion, work and energy, linear momentum, gravity, rigid body equilibrium, and thermodynamics. He defines ‘causalitic’ as causality and analytic. He finds that the PSA increased significantly. In principle, this approach was oriented to facilitating students to develop their abilities in causalitic thinking.

Gopnik and Schulz (2007), and Meder (2006) gave three basic causal models, which are the divergent, convergent and

chain models. Next, Rokhmat (2015) added two other models to them, which are simple and composite. He divided the composite model into simple and chain composites. As a result, there are six models of causal, which are simple, divergent, convergent, chain, simple composite and chain composite causal models; these are abbreviated as SCM, DCM, CCM, ChCM, SCoCM and ChCoCM, respectively.

As described previously, this paper focuses on discussing the six causal models and examples of their use in physics-learning phenomena. The discussion includes the conceptual presentations of the related physics-learning phenomena; and identifying their elements (which are the causes and effects) and which kind of causal model is appropriate. In the first year (of three years) of research, the causalitic-thinking approach was actually implemented in the seven subjects; however, in this paper, we only present its implementation in two subjects, i.e. work and energy, and thermodynamics because, statistically they would have been too many pairs for tcounted and ttable (tcounted, ttable). There are18 pairs per-subject, so for the seven subjects it would have been 128 pairs of tcounted and ttable. Finally, with respect to the title above, this paper is oriented to answer two questions: 1) how is PSA increased in the two subjects as a result of the CTA implementation. and 2) how examples of the causal models in physics learning.

Relating to the previous questions, we focus this literature review on three topics; the CTA, PSA and the causal model in Physics learning.

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Causalitic-thinking Approach (CTA)

An approach is defined as a way of doing something. This paper regards this from the point of view of a learning process. Based on which is more active in the learning between a student and teacher, the approach is divided into two: student- and teacher-oriented approaches. In the former, the teacher has the role to facilitate the students exploring information by themselves. While, in the latter, a teacher is a source of information that they actively transfer to students.

Causal i t ic th inking (CT) i s an abbreviation of ‘causality and analytic thinking’. Paul (2003) divides thinking into eight elements, i .e. generating objectives, proposing questions, applying information, creating a concept, making a conclusion, making assumptions, generating understanding and realising a point of view. However, Gopnik and Schulz (2007) states a philosophical approach to causation theory, which is that it is difference-making, i.e. every cause will create a different effect. The cause must result in, or at least modify, the possibility for an effect to occur. This principle states that some causes are independent from space and time when resulting in an effect. Another principle is that the same initial conditions result in the same phenomenon series. In addition, two principles, Hill (2011) describes one principle of causality, i.e., that one event (a cause) will produce another event (an effect), and if the events are separated by space, they have to be separated by time.

Marzano and Kendall (2008) agreed that analytical thinking is higher-order thinking, while Amer (2005) revealed that analytical thinking is closed to creative thinking. He proposes that analytical thinking is a tool that is useful for understanding a phenomenon. The basic idea of analytical thinking is make a handful of elements, comparing them, give a rank, and finally select the most valuable and discharge the remainder. With respect to CT, analytical thinking refers to how well students can identify the conditions of causes so they result in the determined effect. Kasser (2006) mentioned that to identify, it needs an explanation, and, when establishing the explanation, it has to be presented in terms of facts, concepts, principles, theories and/or laws of physics.

In CT, a student completes some activities that are in line with the causality and analytic thinking. These are activities that are closed to causality thinking such as understanding phenomenon, determining causes, predicting effect and differentiating the causes that are factors of each effect. However, activities that are closed to analytic thinking include identifying the causes that result in an effect, codifying an explanation to correlate cause and effect, and establishing an argument for why the effects happen. To codify the explanation, it has to be presented in terms of facts, concepts, principles, theories and/or laws of Physics, which is closed to the causes and/or effects. Therefore, analytic thinking means determining and applying facts, concepts,

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principles, theories and/or laws of physics, and, finally, they are used for identifying or compiling an explanation of why the effect happens.

The elements of the CT agree with some elements of thinking, especially the elements that are stated by Paul (2003), and Kasser (2006). Congenialities exist between the CT and eight elements from Paul (2003), such as understanding CT in line with generating objectives and generating understanding, determining causes and predicting effects that agree with the generated objective, proposing questions, applying information and creating a concept, and differentiating causes is appropriate to proposing questions and creating concept. Furthermore, there are congenialities between CT and the ideas of identification from Kasser (2006) for at least two elements, i.e. identifying causes and explaining the relation between the cause and effect. Therefore, the elements of CT are in agreement for at least nine among the eleven (81%) elements of thinking described by Paul (2003), and Kasser (2006).

Problem-solving Ability (PSA)

In this paper, the term problem-solving ability (PSA) is deductively derived from several opinions such as Marzano and Kendall (2008), and Marzano and Brown (2009). Marzano and Brown (2009) agreed that it is necessary for students to use their knowledge in problem solving to generate and staunch their opinion. While, Marzano and Kendall (2008) gave recommendation for seven questions to encourage problem solving. The questions include determining

what the objectives are, what the obstacles are, the way to handle obstacles, the best solutions, the real event, the congeniality between the result and solution, and/or the way to change thinking.

Marquardt (2004) explained two approaches to problem solving. The analytic approach is the first and is the approach through which he maintains that a phenomenon has only one solution. However, integrative approach is the second and the approach through which he proposes there are many solutions to one phenomenon. This approach is recommended in order to develop a multi-effect phenomenon. It varies as to whether there are one or more elements of cause in the phenomenon. Through this latter phenomenon, a student is facilitated to identify conditions of all causes and determine all of the possible effects.

Based on the two previous paragraphs, PSA is defined as two things. First, the ability to use knowledge to select and/or predict all effects when solving a phenomenon, and second, the ability to identify how causes result in each effect.

In general, PSA is defined as having the ability to solve a problem. With respect to causalitic thinking, PSA includes six indicators, i.e. understanding, selecting, differentiating, determining, applying and identifying (Gopnik & Schulz, 2007; Meder, 2006; Paul, 2003). Understanding is defined as the ability to know what the idea behind a problem is; selecting is the ability to determine which elements (in a problem) are the causes and which are the effects. A cause, statistically, is an independent variable and

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an effect is a dependent variable. Next, differentiating is defined as the ability to differentiate which cause (or causes) are factors of the effect. Determining is defined as the ability to establish the concepts, principles, theories and/or laws of physics that are related to each effect. Applying is defined as the ability to apply the concepts, principles, theories and/or laws of physics that explains why each effect occurs. And, finally, identifying is the ability to identify the conditions of the cause (or causes) so that it (they) results in the effect.

There is conformity between CT and PSA; to analyse a phenomenon and categorise the causes and effects needs an understanding of the idea and objective of the phenomenon, as well as the consideration and ability to analyse the differences. The three aforementioned needs (understanding, consideration and ability) are included in analytic thinking. Thus, analytic thinking has a significant role in causality thinking. This fact is in line with the findings of Amer (2005), Cohen (2000), Hamilton (2001), Paul (2003) and Zschunke (2000).

T h e t h r e e i n d i c a t o r s o f P S A (understanding, selecting and differentiating) and the interpretation of problem solving are summarised in the indicators for analytic thinking from Amer (2005), Cohen (2000), Hamilton (2001) and Zschunke (2000). The fourth and fifth indicators (determining and applying) support the ability to identify causes.

From the previous descriptions, it can be concluded that the ability for causality and

analytic thinking supports PSA. Causality thinking directly supports the ability to select and/or predict effects in a phenomenon. However, analytic thinking supports the ability to identify how causes have the possibility of resulting in the determined effect. Thus, causality and analytic thinking supports PSA.

Causal Models in Physics Learning

Causal-thinking model: the three ideas with respect to the causal model of thinking from Gopnik and Schulz (2007), and Meder (2006) can be developed into six models. The models include three basic models (the divergent, convergent and chain models) and three other models from the development of the basic models (simple, simple composite, and chain composite models) (Figures 1 and 2).

Figure 1 shows four basic causal models; the circles represent the variables of events, while the arrows express the direction of cause-effect. The models are: (a) the SCM, where one cause X influences one effect Y; (b) the DCM, where one cause X influences two or more effects Y1, Y2 and so on; (c) the CCM, where two or more causes X1, X2, and so on influence one effect, Y; (d) the ChCM, where one initial cause Xinfluences one in-between effect Y, which influences one final effect Z. In addition, Figure 2 shows the combination of the four models (SCM, DCM, CCM and ChCM) into two further models: (a) the SCoCM and (b) the ChCoCM. In the SCoCM, two or more causes X1, X2, and so on influence two or

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more effects Y1, Y2 and so on, and in the ChCoCM, two or more initial causes X1, X2 and so on influence two or more in-between

effects Y1, Y2 and so on, which influence two or more final effects Z1, Z2 and so on.

Figure 1. One Simple Causal Model (SCM) (Rokhmat, 2013; 2015; Rokhmat, Marzuki, Hikmawati, & Verawati, 2017) and three Basic Causal Models (Gopnik & Schulz, 2007; Meder, 2006)

and so on; (c) the CCM, where two or more causes X1, X2, and so on influence one effect, Y; (d)

the ChCM, where one initial cause X influences one in-between effect Y, which influences one

final effect Z. In addition, Figure 2 shows the combination of the four models (SCM, DCM,

CCM and ChCM) into two further models: (a) the SCoCM and (b) the ChCoCM. In the SCoCM,

two or more causes X1, X2 and so on influence two or more effects Y1, Y2 and so on, and in the

ChCoCM, two or more initial causes X1, X2 and so on influence two or more in-between effects

Y1, Y2 and so on, which influence two or more final effects Z1, Z2 and so on.

Figure 1. One Simple Causal Model (SCM) (Rokhmat, 2013; 2015; Rokhmat, Marzuki,

Hikmawati, & Verawati, 2017) and three Basic Causal Models (Gopnik & Schulz, 2007; Meder,

2006)

(d)

2

Empirical)ChainCausalModel

(c)

ConvergentCausalModel(CCM)

(a)

2

X Y

(b)

DivergentCausalModel(DCM)

X

Y1 Y2

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X1X2

... Y

X

Y Z

(a)

X1

X2

...

Y1

Y2

...

(b)

...

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Y1

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...Figure 2. Composite Causal Models (CoCM) (Gopnik & Schulz, 2007; Rokhmat, 2015; Rokhmat, Marzuki, Hikmawati, & Verawati, 2017) (a) Simple (SCoCM) and (b) Chain (ChCoCM)

and so on; (c) the CCM, where two or more causes X1, X2, and so on influence one effect, Y; (d)

the ChCM, where one initial cause X influences one in-between effect Y, which influences one

final effect Z. In addition, Figure 2 shows the combination of the four models (SCM, DCM,

CCM and ChCM) into two further models: (a) the SCoCM and (b) the ChCoCM. In the SCoCM,

two or more causes X1, X2 and so on influence two or more effects Y1, Y2 and so on, and in the

ChCoCM, two or more initial causes X1, X2 and so on influence two or more in-between effects

Y1, Y2 and so on, which influence two or more final effects Z1, Z2 and so on.

Figure 1. One Simple Causal Model (SCM) (Rokhmat, 2013; 2015; Rokhmat, Marzuki,

Hikmawati, & Verawati, 2017) and three Basic Causal Models (Gopnik & Schulz, 2007; Meder,

2006)

(d)

2

Empirical)ChainCausalModel

(c)

ConvergentCausalModel(CCM)

(a)

2

X Y

(b)

DivergentCausalModel(DCM)

X

Y1 Y2

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X1X2

... Y

X

Y Z

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X1

X2

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Y1

Y2

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(b)

...

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Y1

Y2

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METHODS

This research (for the first of the three years) used a mixed methods of embedded, experimental design with a two-phase approach. This method uses a qualitative method as the main approach with a quantitative method embedded in it. The

process for this research included four main activities; first, analysing the subject matter; second, designing the instruments; third, validating the instruments (expert and empiric); and forth, analysing and interpreting the instruments (Creswell & Clark, 2007) (Figure 3).

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Figure 3 is for the first year’s (of three years) research design for one group pre-test–post-test (Suharsaputra, 2012) as a modification of Creswell and Clark (2007). In this design, the quantitative data are embedded in the qualitative data. The qualitative data were observed in analysing the subject, developing the instruments, validating the instruments, as well as in analysing and interpreting the results of this research. However, the quantitative data were collected during pre-test and post-test. The tests were conducted in the process of empirical instrument validation. A qualitative approach was needed to analyse the data including from filling in the attitude scale, observation and interviews. These data are related to the causal models and their characteristics. Furthermore, a quantitative approach was needed to analyse the results (increase) in PSA. Finally, information about the superiority and restrictiveness of the causal models, and about the PSA increase were useful to make recommendations to develop better instruments and for its implementation.

The subjects of this research were the students of the Physics Educational

Programme at one university in Mataram in the 2015/2016 semester year. The sample included 49 students (ten among them males). In the empirical validation, we agglomerated the students into ten groups based on the results of the initial test; nine groups possessed five members, while the other one possessed four members. In the analysis, the subjects were agglomerated into three (approximately homogeneous) groups. Students with ranks 1 to 9 became group one, ranks 10 to 40 became group two, and, finally, ranks 41 to 49 become group three. We informed the first agglomeration but we did not announce the second one. Next, we named the first and the third groups, respectively, as the high (Hi) and low (Lo) groups. The aim of using these two groups was to analyse the increase in PSA while qualitatively validating the instruments. We gathered information on all students. Non-parametric statistic (test of location for two dependent groups), the Wilcoxon signed-ranks test (Minium, King, & Bear, 1993) was used to analyse the PSA increase and its N-gain difference between the Lo and Hi groups.

Figure 3. Two-Phase Embedded Experimental Design

Figure 2. Composite Causal Models (CoCM) (Gopnik & Schulz, 2007; Rokhmat, 2015;

Rokhmat, Marzuki, Hikmawati, & Verawati, 2017) (a) Simple (SCoCM) and (b) Chain

(ChCoCM)

METHODS

This research (for the first of the three years) used a mixed methods of embedded, experimental

design with a two-phase approach. This method uses a qualitative method as the main approach

with a quantitative method embedded in it. The process for this research included four main

activities; first, analysing the subject matter; second, designing the instruments; third, validating

the instruments (expert and empiric); and forth, analysing and interpreting the instruments

(Creswell & Clark, 2007) (Figure 3).

Figure 3. Two-Phase Embedded Experimental Design

Figure 3 is for the first year’s (of three years) research design for one group pre-test–post-test

(Suharsaputra, 2012) as a modification of Creswell and Clark (2007). In this design, the

InitialStudy

1

Validation(Expert&

1

Analysisandinterpretationofoutput:draftof10PT,20SWS,

StudentBookofFundamentalPhysicsIwithCTA,Hypothetical

CausaliticLearningModel(HCLM)SimpleCausal

Model(SCM)

AnalysisofSubject

Developmentof“Causalitic”Thinking

Instruments

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RESULTS

Increase of Problem-solving Ability (PSA)

The increase of PSA was obtained from calculating post-test minus pre-test. Its significance was determined using the

values of tcounted (value of t calculated from Wilcoxon signed rank test) and ttable (value of t from the table with a significance level 5%). We rejected the null hypothesis if the tcounted equals or is less than ttable (Minium et al., 1993).

Table 1 Problem-solving ability (PSA) (%) from Pre-test (Pe) & Post-test (Po) for the Low (Lo) group

Subject Indicators of Problem-solving Ability (IPSA)IPSA-1 IPSA-2 IPSA-3 IPSA-4 IPSA-5 IPSA-6

Pe Po Pe Po Pe Po Pe Po Pe Po Pe PoWork and energy 11 28 6 28 0 17 11 33 0 17 0 19Thermodynamics 22 96 33 63 0 30 11 74 0 30 0 26

Table 2 Problem-solving ability (PSA) (%) from Pre-test (Pe) & Post-Test (Po) of High (Hi) group

Subject Indicators of Problem Solving Ability (IPSA)IPSA-1 IPSA-2 IPSA-3 IPSA-4 IPSA-5 IPSA-6

Pe Po Pe Po Pe Po Pe Po Pe Po Pe PoWork and energy 39 100 11 56 0 56 33 100 0 67 0 43Thermodynamics 30 89 26 63 4 33 26 82 7 41 4 30

Tables 1 and 2 show the percentage of PSA from the pre-test and post-test, respectively, for the Lo and Hi groups for the subjects of work and energy, and thermodynamics;

visually, all indicators of the PSA (IPSA-1 to IPSA-6) increased. Table 3 indicates that all of the normal gains (Lo and Hi groups, and for the subjects) are positive.

Table 3 Normal gain of PSA for Low (Lo) group and High (Hi) group

Subject Indicators of Problem Solving Ability (IPSA)IPSA-1 IPSA-2 IPSA-3 IPSA-4 IPSA-5 IPSA-6

Lo Hi Lo Hi Lo Hi Lo Hi Lo Hi Lo HiWork and energy .19 1 .24 .50 .17 .56 .25 1 .17 .67 .19 .43Thermodynamics .95 .84 .45 .50 .30 .31 .71 .75 .30 .36 .26 .27

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Next, Tables 4 and 5 reveal the list of tcounted (tc), the number of effective pairs (n) and ttable (tt) (for the PSA increase and its gain difference) for each subject. Pairs of tcounted and ttable (tcount, ttable) for IPSA-1 to IPSA-6 for the Lo group are (0,-), (0,-), (0,-), (0,-), (0,-), (0,2) for work and energy, and (0, 5), (0, -), (0, 2), (0, 3), (0, 2), (0, 0) for thermodynamics. While, for the Hi group, the pairs are (0,5), (0,2), (0,2), (0,3), (0,3), (0,2) for work and energy, and (0,3), (0,3), (0,0), (0,5), (0,0), (0,-) at thermodynamics. Finally, the pairs of tcounted and ttable (tcounted,

ttable) for the PSA gain differences are (0,5), (4,5), (3,2), (0,3), (3,5), (4.5,5) at work and energy, and (3,-), (9.5,3), (12,2), (12,5), (12,3), (9,0) for thermodynamics. The value of ttable is related to the number of effective data pairs (for six, seven, eight and nine pairs, the ttablerespectively are 0, 2, 3 and 5). It is clear that, there are 17 pairs (for the pre-and post-test difference) and nine pairs (for the N-gain difference) of tcounted and ttable, with tcounted<ttable for all groups and subjects, and so the null hypothesis was rejected.

Table 4 List of tcounted (tc), number of effective data pairs (n) and ttable (tt) resulting from the Wilcoxon signed rank test of each PSA indicator for work and energy

Attribute Indicators of Problem Solving Ability (IPSA)IPSA-1 IPSA-2 IPSA-3 IPSA-4 IPSA-5 IPSA-6

tc n tt tc n tt tc n tt tc n tt tc n tt tc n tt

Low group 0 3 - 0 4 - 0 3 - 0 3 - 0 3 - 0 7 2High group 0 9 5 0 7 2 0 7 2 0 8 3 0 8 3 0 8 3N-gain diff. 0 9 5 4 9 5 3 7 2 0 8 3 3 8 3 4.5 8 3

Table 5 List of tcounted (tc), number of effective data pairs (n) and ttable (tt) resulting from the Wilcoxon signed rank test of each PSA indicator for thermodynamics

Attribute Indicators of Problem Solving Ability (IPSA)IPSA-1 IPSA-2 IPSA-3 IPSA-4 IPSA-5 IPSA-6

tc n tt tc n tt tc n tt tc n tt tc n tt tc n tt

Low group 0 8 3 0 5 - 0 7 2 0 8 3 0 7 2 0 6 0High group 0 8 3 2.5 8 3 0 6 0 0 9 5 0 6 0 0 5 -N-gain diff. 0 2 - 9.5 8 3 12 7 2 12 9 5 12 8 3 9 6 0

Examples of the Causal Models in Physics Learning

Examples of causal models revealed the causes and effects in Physics that have the

same relation as for one of the six models. The number of causes and effects for each physics phenomenon is basically indefinite. However, we could restrict them with a specific question, such as we can ask what

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will be a free body’s experience with respect to its movement when a constant force acts to it. For this phenomenon, a constant force acts on a free body as the cause, while movement with constant acceleration is its effect.

The previous example is the pair of one cause and one effect, so is an SCM. For the DCM, we restrict it to ask for all possible happenings, both constant or change with respect to velocity, speed and acceleration of an object that is moving circling uniformly around a point, P. This phenomenon has one cause (the object moves uniformly in a circle around a point P) and three effects (its velocity changes uniformly, its speed is constant and its acceleration changes uniformly). For example, f the CCM, we can confine this to only ask for all possible directions of each velocity change when a ball moving, circling uniformly around point P with a constant speed v and where its velocity at four different positions (1, 2, 3 and 4) is always on a tangent to its orbit at that point. This phenomenon has five causes (moving uniformly in a circle around point P, and four vector velocities at points 1, 2, 3, and 4) and one effect (each velocity change is always towards point P).

Next, for the physics phenomenon in the ChCM, we can ask for all possible interaction forces (in series) between the block and the table when we put a block, which has weight W, on the table. In this example, there is one cause (the weight of block W), one in-between effect (the block presses the surface of the table downward with force Fdownward) and one final effect (the

surface of table holds back the block with normal force upward, N). In the SCoCM, for example, we may restrict this to asking for all possibilities where vehicles P and Q are in a side-by-side position when vehicle P is at rest athwart line L then moves to the right with constant acceleration a and, after few minutes, another vehicle Q, which is moving, also to the right, with constant velocity v crosses line L, and the trajectory of P and Q is side-by-side, straight and quite long. This physics phenomenon has three causes (vehicle P at rest athwart line L moves to the right with constant acceleration a, vehicle Q also moves to the right with constant velocity v across line L, and P crosses line L a few minutes before Q) and also three effects (P and Q will never be in a side-by-side position, will be in a side-by-side position one time, and will be in a side-by-side position two times).

Finally, in the ChCoCM, we can confine this to asking for all possible happenings that a block will experience with respect to the type of friction force, the shifting of its normal force, and whether the block remains at rest or moves (translational or rotational) when a homogeneous block M, with weight W, width a and height2a, is at rest on a table and a force F (its force line at a height of h) pulls it to the right, and it is known that the surfaces of both block and table are coarse (with static and kinetic coefficients of μs and μk, respectively, and μs> μk). In this example, there are eight causes, three in-between effects and three final effects. The eight causes are (1) weight of block M of W; (2) the size of the block, width a and

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height 2a; (3) horizontal force F to the right; (4) the work line of F at height h above the surface of the table; (5) the static coefficient μs; (6) the kinetic coefficient μk; (7) value μs is greater than μk; and (8) the surface of the table holds the block with normal force upward, N, through the vertical symmetry line of the block. Next, the three in-between effects are (1) the block experiences a static friction force fs (to the left), (2) the block experiences a kinetic friction force fk (to the left), and (3) the normal force N shifts (to the right) so it ends up on the right side of the vertical symmetry line of the block. Finally, the three final effects are (1) the block M remains at rest, (2) the block M shifts to the right, and (3) the block M rolls in a clockwise direction.

It should be noted that the number of causes for a phenomenon is basically not absolute. For example, we may assume that causes 5, 6, and 7 are only one cause, i.e. the static and kinetic coefficients are μs and μk, with μs being greater than μk.

DISCUSSION

Modus of the Causal Model in Physics

What we commonly find in physics problems are CCMs (with multi-cause and mono-effect) due to there being only one answer to the problem. To increase creative thinking ability, problems with more than one correct answer (multi-effects) need to be developed. This agrees with causal models DCM, SCoCM or ChCoCM, but, among them, the SCoCM is the easiest to develop. In the SCoCM, we may arrange one or more of its causes as a variable and it is suggested to

restrict them so that number of its effects is adjusted to the level of difficulty to make it possible for a learner to answer the problem. In addition to the number of effects, we can also direct the depth of its arguments by controlling on which concept, principle, theory and/or law they are based.

Relation of this Research to Some Previous Research

The three aforementioned models (DCM, SCoCM and ChCoCM) lineally encourage creative thinking which indicates that fluency, flexibility and/or originality will result from an open-ended task (Meyer & Lederman, 2015). However, Anwar, Aness, Khizatr and Muhammad (2012) stated that in addition to the three effects, the models also encourage elaboration. Fluency shows how many answers a learner has predicted, flexibility is related to how high a level of difficulty has been designed, originality is indicated from the additional answers written by a learner and, finally, elaboration is shown from how learners build their ideas. In addition, the models also have a similarity to the strategy used by Escudero et al. (2009). They facilitated undergraduate students investigating all possible knowledge (concepts and theories) about the phenomena (solid and hollow body, ball and cylinder, rolling on inclined coarse surface) through writing as many answers as possible about the knowledge they have gained).

While, Baser (2006) through conflict cognitive instruction (CCI) facilitated students to discuss contradictory facts

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(resulting from experiments) in relation to their previous conceptions. This instruction is in line with learning through CTA. Both foster the development of critical thinking, which needs analytical and causality thinking. Another conformity is that this CT develops a meta-concept, which also Yürük (2007) found in his research.

Effectiveness of the Causal Model in Physics Learning with a Causalitic-Thinking Approach (CTA).

The effectiveness of the causal model in physics learning with a CTA is indicated by an increase in PSA. Among the 24 pairs of tcounted and ttable for each IPSA in the Lo and Hi groups, and for two subjects, 17 pairs (71%) indicate tcounted<ttable, which means that the PSA of students increased significantly. Furthermore, among 12 pairs of tcounted and ttable for the N-gain difference between Lo and Hi groups, four pairs indicate tcounted<ttable, which means that the PSA increase for the Lo and Hi students was only 33%.

This fact means that using a causal model in the learning with CTA was effective in increasing the PSA of students, and the increases were not different between the Lo and Hi groups (it gives the same advantage for the Lo and Hi students). However, its final attainment was high, being only 8% in the Lo group and 33% in the Hi group. This means that the instrument still needs perfecting.

The positive impact of using the causal model in learning with CTA on the PSA agrees with the relation between the CTA and PSA, which was summarised

from the statements of some experts. The experts include Amer (2005), Cohen (2000),Hamilton (2001), Paul and Elder (2003), and Zschunke (2000).

Restrictiveness of the Causal Model with CTA in Physics Learning.

There are some restrict ions on the implementation of learning by using causal model with CTA. One of which is that it needs quite a long time to implement, so the lecturer had less time to discuss students’ work, and it was difficult for students to solve the phenomenon. In addition, regarding the preparation of instruments and their implementation strategy, in general, each phenomenon needs a long description and we did not prepare a hand-out that is suitable for this type of learning. The restrictions did not foster the development of the CTA of students. This is caused by the fact that the process to select and/or deductively predict all possible effects needs initial knowledge.

To reduce the Restrictions of the Causal Model with CTA in learning.

It is advisable to include some stages for perfecting the instruments. Those are preparing a hand-out, using a shorter description of the phenomenon and, for 100 minutes of learning, it may need only one phenomenon to be studied. In addition, based on the final attainment of PSA (on average, this is moderate), it is advisable to design a causal model with the CTA in scaffolding form, i.e. with assistance to facilitate the

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students solving the phenomenon. Examples of the assistance are such as, for the causal model that has more than one cause and/or effect, we inform the students about some of them. In addition, we could also give an example of the explanation of the conditions for each cause so that they would result in the determined effect.

CONCLUSION

A causal model for Physics learning with CTA has been developed, which is significantly effective in increasing the PSA of students for the subsubjects of work and energy, and thermodynamics. The models are simple, divergent, convergent and chain causal, plus the composites of these four models, i.e. simple and chain composite causal models.

The PSA consists of six abilities, i.e. the ability to understand a problem; select causes and effects; differentiate which causes are the variables of the determined effect; determine the concepts, principles, theories and/or laws of physics; apply the concepts, principles, theories and/or laws of physics to identify the causes; and finally, identify how the conditions of all causes result in the determined effect. In addition, to increase the effectiveness of its instrument, it needs some actions for perfecting the instruments, which includes perfecting the design and strategy for implementation.

ACKNOWLEDGMENTS

We gratefully acknowledge the staff leader of the Ministry of Research, Technology,

and High Education of Indonesia, the research institution, and all staff leaders in Mataram University. We also acknowledge our families, and appreciate all of the help given by our colleagues and all first year Physics education students of year 2015/2016, who have helped us in the completion of this project.

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