This guide sets out how to design, run and report a case study in software engineering to a standard that survives examiner scrutiny, written for Master’s and PhD candidates in Malaysia. It is based on how I assess and supervise postgraduate work at UPSI.

When Case Study Research Is the Right Method

Choose a case study when all three of these are true. If any one fails, another method will usually serve you better.

• Your question is about how or why something happens, not how much or how often.
• You cannot control the behaviour of the people or systems involved.
• The context genuinely matters, so removing it would change the answer.

If you want to measure whether technique A outperforms technique B under controlled conditions, run an experiment instead. If you want to summarise what is already known across published studies, run a systematic literature review. The trade-offs between these routes are compared in SLR versus experimental research for AI postgraduates.

The Four Types of Case Study Purpose

• Exploratory: you are looking for what is happening and generating ideas for later study. Common at the start of a PhD.
• Descriptive: you are documenting a situation in detail without explaining causes.
• Explanatory: you are seeking to explain why something occurs, which is the most demanding and the most defensible at doctoral level.
• Improving: you are trying to change the situation and evaluate the change, which overlaps with action research.

State your purpose explicitly in the methodology chapter. Examiners frequently challenge candidates who describe an exploratory study but then make explanatory claims in the conclusion.

Designing the Case Study: Five Decisions to Document

1. Define the case and its boundary

The case is the unit of analysis: one development team, one migration project, one product line, one university department adopting a tool. Write down what is inside the boundary and what is outside it. A vague boundary is the most common weakness in student case studies.

2. Choose single or multiple case design

A single case is justified when it is critical, unique, revelatory or longitudinal. Multiple cases give stronger analytical generalisation because you can look for patterns that repeat across settings. For a Master’s dissertation one well-documented case is usually sufficient. For a PhD, two to four cases are more common.

3. Select the data sources

Case study strength comes from combining sources rather than relying on one. Typical software engineering sources include semi-structured interviews, direct observation of stand-ups or reviews, repository and issue-tracker data, internal documentation, and tool telemetry.

4. Plan the analysis before you collect

Decide in advance whether you will use thematic coding, pattern matching against a proposed explanation, or cross-case synthesis. Writing the analysis plan into the protocol prevents the common failure of ending up with 30 hours of interviews and no defensible way to interpret them.

5. Address ethics and confidentiality early

Company data, employee interviews and production logs all raise consent and confidentiality questions. Malaysian universities require ethics clearance before data collection begins, and Malaysian organisations will usually want a non-disclosure agreement. Build the approval timeline into your Gantt chart, because this step routinely delays candidates by two or three months.

Building Validity Into the Design

Case study research is often criticised for being subjective. The response is not to argue, but to build validity checks into the protocol and report them openly.

• Construct validity: use multiple sources for each key claim, and have participants review your account of what they said.
• Internal validity: for explanatory studies, test rival explanations against the evidence rather than confirming your first hypothesis.
• External validity: describe the context in enough detail that a reader can judge which other settings your findings might apply to. Case studies generalise to theory, not to populations.
• Reliability: maintain a case study database and a written protocol so another researcher could repeat your steps.

Reporting: What Examiners Look For

• A clear statement of the case, the boundary, and why this case was selected.
• A protocol summary, including interview guides and coding schemes, usually placed in the appendix.
• Enough context description for the reader to interpret the findings, while respecting confidentiality.
• A visible chain of evidence linking raw data to codes, codes to themes, and themes to conclusions.
• An honest limitations section that names the threats to validity you could not remove.

The chain of evidence is the part most candidates underestimate. If an examiner cannot trace a conclusion back to a specific quotation or log entry, the finding will be treated as opinion.

Common Mistakes in Student Case Studies

• Calling a single set of interviews a case study without defining a case at all.
• Collecting rich data then reporting only descriptive summaries, with no theoretical contribution.
• Treating one company as representative of an entire industry.
• Ignoring negative evidence that contradicts the emerging story.
• Leaving ethics approval until after data collection has started.

Case-study designs appear frequently in applied AI doctorates. For context on how method choice fits into the wider programme, from proposal to viva, see the complete guide to a PhD in AI.

Frequently Asked Questions

Is case study research accepted for a PhD in software engineering?

Yes. Case study research is a recognised empirical method in software engineering and is widely used in doctoral work, provided the design is explicit and validity threats are addressed. Weak case studies are rejected for poor design, not for being case studies.

How many cases do I need?

There is no fixed number. A single case is defensible when it is critical, unique or revelatory. Multiple cases strengthen analytical generalisation, and two to four is common at doctoral level in Malaysia.

What is the difference between a case study and action research?

In a case study you observe without deliberately changing the situation. In action research you intervene and study the effect of your own intervention. If you are introducing a tool and measuring what happens, you are closer to action research.

Can I combine a case study with a systematic literature review?

Yes, and it is a strong combination. The review establishes what is already known and exposes the gap, and the case study supplies the fresh empirical evidence. Many Malaysian postgraduate theses use exactly this structure.

How many interviews are enough?

Stop when new interviews stop producing new codes, which is usually described as saturation. In practice, 8 to 15 interviews per case is a common range in software engineering, but you must justify your own stopping point with evidence.

Who is Dr Hariz?

Dr Muhamad Hariz Bin Muhamad Adnan holds a doctorate in artificial intelligence and is a Senior Lecturer at the Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris (UPSI). He supervises postgraduate research in AI and computing and works as an HRD Corp certified AI trainer in Malaysia.

Getting Your Design Reviewed

Most case study problems are cheaper to fix at the protocol stage than after data collection. If you are shaping a Master’s or PhD design in AI, computing or software engineering, see the postgraduate supervision page or get in touch to talk through your research question. If you are still at the proposal stage, start with the guide to writing an AI research proposal for Master’s and PhD study in Malaysia, and plan ahead for publishing in a Scopus indexed journal.

For worked examples of how these design choices play out in a real programme of work, see the ongoing and completed research projects Dr. Hariz leads at UPSI.

This guide explains how to run an SLR from planning to write-up, in plain language, for Malaysian Master’s and PhD students who need a defensible methodology chapter.

What Makes a Review “Systematic”

Three things separate a systematic review from a narrative one.

A protocol written in advance. You decide your research questions, search strategy, inclusion and exclusion criteria, and quality assessment rules before you start reading. This is what stops you from unconsciously selecting only the papers that agree with you.

A documented, reproducible search. Every database, every search string, every date is recorded. A reader should be able to re-run your search and get a comparable set of results.

Transparent selection and synthesis. You report how many papers you found, how many you excluded and why, and how you combined the findings. Nothing is hidden in the gap between “I read a lot” and “therefore”.

The Three Phases of an SLR

Phase 1: Planning the review

Start by confirming the review is actually needed. If a recent, well-conducted review already answers your question, your contribution should be something else. Then write the protocol, which should contain your research questions, the databases you will search, your search strings, your inclusion and exclusion criteria, your quality assessment checklist, and your data extraction form.

Your research questions drive everything. In software engineering, a common structure is to ask what has been studied, how it has been evaluated, and what remains unresolved. Keep the number small: two to four questions is usually enough for a Master’s or PhD chapter.

Phase 2: Conducting the review

Run the search across the main digital libraries used in computing: IEEE Xplore, ACM Digital Library, Scopus, Web of Science and SpringerLink. Export everything into a reference manager so you can deduplicate cleanly. Screen by title and abstract first, then by full text. Record the count at each stage, because you will need those numbers for your PRISMA-style flow diagram.

Quality assessment comes next. Score each remaining study against a short checklist: is the research question clear, is the method described well enough to repeat, is the sample or dataset described, are threats to validity discussed, are the conclusions supported by the data. Studies that fail badly are excluded, and you report why.

Finally, extract data using a consistent form so every paper is recorded the same way: year, venue, research type, technique used, dataset, evaluation method, and the finding relevant to each research question.

Phase 3: Reporting the review

Synthesis is where the value is created. Group studies by theme, technique or outcome rather than describing them one by one. A chapter that reads as a list of paper summaries is a signal that synthesis has not happened yet. Report both what the literature agrees on and where it conflicts, and state honestly what could not be concluded from the available evidence.

Building a Search String That Works

Break your research question into concepts, list synonyms and alternative spellings for each concept, join the synonyms with OR, and join the concepts with AND. For example, a review on machine learning for defect prediction would combine a “machine learning” concept group, a “software defect” concept group and a “prediction” concept group.

Test the string on one database first. If it returns tens of thousands of results, your concepts are too broad. If it returns fewer than thirty, they are too narrow or your synonyms are incomplete. Adjust before running the full search, and record the final version of every string in an appendix.

Common Mistakes That Weaken an SLR

Searching only Google Scholar. It is useful for validation but is not a substitute for indexed digital libraries with reproducible query syntax.

Writing the protocol after the search. Examiners notice when inclusion criteria appear to have been designed around the papers already collected.

Skipping quality assessment. Without it, a weak conference paper carries the same weight as a rigorous empirical study.

Describing instead of synthesising. If your findings section could be reordered without losing meaning, it is a list, not a synthesis.

Ignoring threats to validity. Every review has them: publication bias, language restrictions, the date the search was run. State them rather than hoping nobody asks.

Is an SLR the Right Methodology for You?

An SLR suits research questions about the state of knowledge in a field, and it produces a strong first publication because the output is self-contained. It is less suitable if your contribution depends on building and evaluating a new system, in which case an experimental or design-science approach fits better. I compare the two paths in more detail in SLR vs Experimental Research: Choosing a Methodology for Your AI Postgraduate Study.

Many students do both: an SLR to map the field and identify a gap, then an experimental study addressing that gap. If you are still shaping your topic, research gaps in AI in education is a useful starting point, and how to write a strong AI research proposal shows how the review feeds into your proposal.

Kitchenham and Charters (2007): Guidelines for Performing Systematic Literature Reviews in Software Engineering

Almost every SLR in computing traces its method back to one document: Guidelines for Performing Systematic Literature Reviews in Software Engineering by Barbara Kitchenham and Stuart Charters, published in 2007 as EBSE Technical Report EBSE-2007-01 (Keele University and University of Durham, version 2.3). It is the reference examiners in Malaysia expect you to cite when you describe your review protocol, and the three-phase structure explained above (planning, conducting, reporting) comes directly from it.

What the report gives you that this article does not: the full protocol template, worked examples of search strings, quality-assessment checklists for different study types, data-extraction forms and a reporting structure for the final review. Read this guide first for the overall logic, then use the report as the detailed rulebook while you write your protocol.

Download the Kitchenham 2007 guidelines PDF

You can download the Kitchenham and Charters (2007) guidelines PDF here (EBSE Technical Report EBSE-2007-01). It is also listed, together with the PRISMA 2020 statement and Dr Hariz’s SLR steps slides, on the free resources for postgraduate students page. Cite it as: Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering (EBSE Technical Report EBSE-2007-01). Keele University and University of Durham.

Frequently Asked Questions

How long does a systematic literature review take?

For a single postgraduate student, four to six months is realistic for a full SLR, with the screening stage usually taking the longest. Working in a pair speeds up screening considerably because two independent screeners are good practice anyway.

How many papers should a systematic literature review include?

There is no fixed number. A well-scoped SLR in software engineering typically ends with somewhere between 30 and 80 primary studies. What matters is that your inclusion and exclusion process is defensible, not that you reach a target count.

What is the difference between an SLR and a mapping study?

A systematic mapping study answers broader questions and classifies the literature to show where research activity is concentrated. An SLR answers narrower questions and synthesises evidence to reach a conclusion. Mapping studies are often a good first step when a field is unfamiliar.

Can I publish my systematic literature review?

Yes, and many students do. Review articles are welcome in indexed journals when they are rigorous and current. See how to publish in Scopus journals as a Malaysian postgraduate for the submission process.

Can AI tools help with a systematic literature review?

They can help with screening support, summarising abstracts and organising extracted data, which saves real time. They cannot decide inclusion for you, and any AI-assisted step must be declared in your methodology. Every claim you keep must be verified against the original paper.

Where can I download the Kitchenham guidelines for systematic literature reviews in software engineering?

The 2007 EBSE technical report by Kitchenham and Charters is linked in the download section of this article and on the free resources page. If you are using it for a Malaysian Master’s or PhD thesis, pair it with the PRISMA 2020 checklist for reporting and describe your protocol in the methodology chapter before you run the search.

Getting Supervision for Your Review

I am Dr Muhamad Hariz Adnan, a Doctor in Artificial Intelligence and Senior Lecturer at the Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris. I supervise postgraduate research in artificial intelligence, educational technology and digital transformation, and systematic literature reviews are a regular part of that work.

If you are planning an SLR for your Master’s or PhD, see my postgraduate supervision areas or get in touch to discuss your topic.

Reference: Kitchenham, B. and Charters, S. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering. EBSE Technical Report EBSE-2007-01.

A systematic review is not the only empirical route open to you. If your question is about how or why something happens inside a specific organisation, case study research in software engineering is usually the better fit.

Related reading for postgraduate researchers

• Research Proposal Example (Contoh dan Tips)
• Tesis PhD atau Master yang baik dan berkualiti
• Cara menggunakan Zotero dengan MS Word dan Google Scholar

The review methods described here underpin Dr. Hariz’s own work. His research page lists the funded artificial intelligence, optimisation and analytics projects that these protocols were built for.

Systematic reviews are a common first-year milestone for doctoral candidates. If you are planning that route, Dr Hariz’s guide to a PhD in artificial intelligence shows where the literature review sits in the overall doctoral journey.

Ringkasan Pantas: Di Mana Garisan Mula dan Garisan Penamat

Master by Research dan PhD bermula daripada perkara yang sama — sebuah cadangan penyelidikan yang diterima universiti dan seorang penyelia yang bersetuju membimbing anda. Kedua-duanya juga tamat dengan perkara yang sama: sebuah tesis yang dipertahankan dalam viva voce. Yang berbeza hanyalah jarak antara dua garisan itu. Master by Research lazimnya mengambil masa 1.5 hingga 3 tahun, manakala PhD 3 hingga 5 tahun secara sepenuh masa di universiti awam Malaysia.

Garisan Mula: Empat Perkara yang Perlu Ada Sebelum Mendaftar

1. Bidang yang cukup fokus

Kesilapan paling biasa ialah datang dengan bidang yang terlalu luas, contohnya “AI dalam pendidikan”. Itu bukan tajuk, itu kawasan. Tajuk yang boleh diterima ialah sesuatu yang boleh dijawab dengan data dalam tempoh pengajian anda, contohnya kesan penggunaan alat AI generatif terhadap kualiti maklum balas guru dalam satu daerah tertentu.

2. Cadangan penyelidikan (research proposal)

Cadangan penyelidikan ialah dokumen yang menentukan sama ada permohonan anda diterima atau ditolak. Ia perlu menunjukkan jurang kajian yang jelas, persoalan kajian yang boleh dijawab, dan metodologi yang munasabah untuk tempoh pengajian anda.

3. Penyelia yang sepadan

Penyelia yang sepadan bermakna seseorang yang benar-benar aktif dalam bidang anda, bukan sekadar mana-mana pensyarah yang masih ada kuota. Semak penerbitan terkini bakal penyelia sebelum menghantar e-mel, dan nyatakan dengan tepat mengapa kerja beliau berkaitan dengan cadangan anda.

4. Kelayakan dan pembiayaan

Kebanyakan program Master by Research memerlukan ijazah sarjana muda dengan CGPA yang mencukupi, manakala PhD memerlukan ijazah sarjana. Pembiayaan pula boleh datang daripada geran penyelidikan penyelia, biasiswa universiti, atau tajaan agensi. Bincangkan hal ini seawal mungkin — ia mempengaruhi sama ada anda belajar sepenuh masa atau separuh masa.

Perjalanan: Peringkat demi Peringkat

1. Pendaftaran dan pemantapan tajuk — tiga hingga enam bulan pertama biasanya digunakan untuk membaca secara meluas dan menyempitkan tajuk.
2. Pertahanan cadangan — anda membentangkan cadangan penuh di hadapan panel fakulti. Kelulusan di peringkat ini mengunci skop kajian anda.
3. Pengumpulan dan analisis data — peringkat paling panjang dan paling mudah tersasar daripada jadual.
4. Penulisan tesis — jangan tunggu sehingga data siap sepenuhnya. Bab kajian literatur dan metodologi boleh ditulis lebih awal.
5. Penyerahan dan viva voce — pemeriksa dalaman dan luaran menilai tesis, kemudian anda mempertahankannya secara lisan.
6. Pembetulan dan senat — hampir semua calon menerima pembetulan. Ia normal, bukan tanda kegagalan.

Garisan Penamat: Viva dan Selepasnya

Viva bukan ujian ingatan. Pemeriksa mahu melihat sama ada anda memahami had kajian sendiri, boleh mempertahankan pilihan metodologi, dan tahu di mana kedudukan kerja anda dalam bidang tersebut. Persediaan yang paling berkesan ialah membaca semula tesis anda sebagai seorang pengkritik, bukan sebagai penulis. Anda boleh mula dengan tips persediaan menghadapi viva dan tips penting untuk berjaya dalam viva.

Master by Research atau PhD — Mana Satu untuk Anda?

• Pilih Master by Research jika anda mahu menguji sama ada penyelidikan sesuai dengan diri anda, memerlukan kelayakan pascasiswazah dalam tempoh lebih singkat, atau merancang untuk menyambung ke PhD kemudian.
• Pilih PhD jika anda sudah pasti dengan bidang, mensasarkan kerjaya akademik atau penyelidikan, dan bersedia dengan komitmen tiga tahun ke atas.

Perbandingan yang lebih terperinci antara ketiga-tiga peringkat ada dalam artikel beza master, PhD dan ijazah sarjana muda.

Peranan AI dalam Penyelidikan Pascasiswazah Hari Ini

Alat AI kini mempercepatkan kerja saringan literatur, pengurusan rujukan dan penyuntingan bahasa. Namun ia tidak menggantikan pertimbangan penyelidik: anda tetap perlu mengesahkan setiap rujukan, memahami setiap analisis, dan bertanggungjawab sepenuhnya terhadap dapatan. Bagi calon yang mahu menjadikan AI sebagai bidang kajian pula, lihat senarai topik penyelidikan AI untuk pelajar pascasiswazah di Malaysia dan panduan menulis cadangan penyelidikan AI.

Soalan Lazim

Berapa lama Master by Research diambil di Malaysia?

Lazimnya 1.5 hingga 3 tahun sepenuh masa, bergantung pada bidang dan kelancaran pengumpulan data. Mod separuh masa boleh mengambil masa lebih lama.

Bolehkah saya terus ke PhD tanpa Master?

Sesetengah universiti membenarkan penukaran status daripada Master by Research kepada PhD selepas prestasi tahun pertama yang cemerlang. Syaratnya berbeza mengikut universiti, jadi tanya penyelia dan pusat pengajian siswazah lebih awal.

Adakah Master by Research lebih sukar daripada mod kerja kursus?

Ia bukan lebih sukar, tetapi lebih berdikari. Tiada peperiksaan bulanan yang memaksa anda bergerak — disiplin diri dan perbincangan tetap dengan penyelia yang menentukan kemajuan anda.

Siapa Dr Muhamad Hariz Adnan?

Dr Muhamad Hariz Bin Muhamad Adnan ialah pemegang Doktor Falsafah dalam bidang Kecerdasan Buatan dan Pensyarah Kanan di Fakulti Komputeran dan Meta-Teknologi, Universiti Pendidikan Sultan Idris (UPSI). Beliau juga jurulatih AI bertauliah HRD Corp di Malaysia dan menyelia pelajar Master serta PhD dalam bidang AI dan transformasi digital pendidikan.

Ingin Berbincang Tentang Penyeliaan?

Jika anda sedang mempertimbangkan Master by Research atau PhD dalam bidang AI dan pendidikan, semak bidang penyeliaan yang ditawarkan di halaman penyeliaan Dr Hariz atau hubungi beliau untuk perbincangan awal tentang tajuk anda.

Jawapan Ringkas: Siapa yang Patut Sambung Master atau PhD?

Anda patut menyambung pengajian ke peringkat Master atau PhD apabila ada sebab yang jelas di sebalik keputusan itu — sama ada kerjaya anda memerlukan kelayakan tersebut, anda mahu beralih ke bidang baharu, atau anda benar-benar mahu menjawab satu persoalan penyelidikan. Menyambung semata-mata kerana belum ada kerja atau kerana rakan lain menyambung biasanya berakhir dengan pengajian yang tergantung separuh jalan.

Empat Perkara yang Dibincangkan dalam Taklimat Ini

1. Kelayakan dan mod pengajian

Master boleh diambil melalui mod kerja kursus, mod campuran, atau sepenuhnya penyelidikan. PhD di Malaysia pula hampir keseluruhannya berasaskan penyelidikan. Pilihan mod menentukan corak hari-hari anda: kerja kursus bermakna kelas dan peperiksaan, penyelidikan bermakna anda menguruskan jadual sendiri di bawah bimbingan penyelia.

2. Pembiayaan

Antara sumber yang biasa digunakan pelajar tempatan ialah biasiswa universiti, geran penyelidikan penyelia, tajaan majikan, dan pinjaman pendidikan. Perkara penting: tanya tentang pembiayaan sebelum mendaftar, bukan selepas. Ramai calon berhenti pada tahun kedua bukan kerana kajian yang sukar, tetapi kerana tekanan kewangan.

3. Memilih penyelia

Penyelia yang betul lebih penting daripada nama universiti. Semak penerbitan terkini bakal penyelia, tanya berapa ramai pelajar yang sedang diselia, dan pastikan gaya penyeliaan beliau sesuai dengan cara anda bekerja. E-mel pertama anda perlu ringkas: siapa anda, apa yang anda mahu kaji, dan mengapa beliau orang yang tepat.

4. Tajuk dan cadangan penyelidikan

Tajuk yang baik ialah tajuk yang boleh dijawab dalam tempoh pengajian anda dengan data yang benar-benar boleh anda perolehi. Panduan lengkap menulis cadangan ada dalam artikel cara menulis cadangan penyelidikan untuk Master dan PhD.

Garis Masa Realistik

• 3–6 bulan sebelum mendaftar — kenal pasti bidang, cari penyelia, siapkan draf cadangan.
• Tahun pertama — pemantapan tajuk, kajian literatur, pertahanan cadangan.
• Tahun kedua hingga ketiga — pengumpulan data, analisis, penulisan bab.
• Tahun akhir — penyerahan tesis, viva voce, pembetulan.

Soalan Lazim

Bolehkah saya sambung Master atau PhD sambil bekerja?

Boleh, melalui mod separuh masa. Namun jangkakan tempoh pengajian yang lebih panjang dan perlu ada persefahaman awal dengan majikan serta penyelia tentang jadual perbincangan dan pengumpulan data.

Perlukah saya ada penerbitan sebelum memohon?

Tidak wajib untuk Master. Untuk PhD ia menjadi kelebihan, dan bagi kebanyakan universiti penerbitan diperlukan sebelum penyerahan tesis — bukan sebelum kemasukan. Rujuk panduan menerbitkan makalah dalam jurnal berindeks Scopus.

Apa beza Master by Research dengan mod kerja kursus?

Mod kerja kursus berteraskan kelas dan penilaian berterusan; Master by Research berteraskan satu kajian panjang dan tesis. Penjelasan penuh ada dalam artikel Master by Research dan PhD: garisan mula dan penamat.

Siapa Dr Muhamad Hariz Adnan?

Dr Muhamad Hariz Bin Muhamad Adnan ialah pemegang Doktor Falsafah dalam bidang Kecerdasan Buatan dan Pensyarah Kanan di Fakulti Komputeran dan Meta-Teknologi, Universiti Pendidikan Sultan Idris (UPSI). Beliau merupakan jurulatih AI bertauliah HRD Corp di Malaysia dan menyelia pelajar Master serta PhD dalam bidang AI dan transformasi digital pendidikan.

Langkah Seterusnya

Jika taklimat ini menjawab sebahagian persoalan anda, langkah berikutnya ialah menyemak bidang penyeliaan yang ditawarkan di halaman penyeliaan, membaca perkara yang perlu anda tahu sebelum menyambung Master dan PhD, kemudian hubungi Dr Hariz untuk berbincang tentang tajuk anda.

Ada juga yang keliru dengan research proposal apabila nak memulakan pengajian Master. Mari saya terangkan…

Apa itu Research Proposal?

Research proposal bertujuan untuk mendapatkan kelulusan dari sesebuah institusi untuk memulakan atau meneruskan sesuatu kajian.  Panel-panel akan menilai kesesuaian tajuk, topik dan kesesuaian kajian kita jika boleh diteruskan atau perlukan perubahan.

Apa yang panel lihat semasa kita membentangkan research proposal ialah:

• Isi kandungan proposal
• Cara penulisan
• Tatabahasa
• Kesesuaian kajian
• Kemahiran pelajar membuat pembentangan

Sebelum pelajar mendaftar Master di sesebuah universiti, pelajar perlu menyediakan proposal yang ringkas. Tetapi, apabila pelajar sudah mendaftar sebagai pelajar Master di universiti, mereka perlu untuk mempertahankan kajian mereka melalui research proposal yang lebih lengkap dan menunjukkan kemampuan menjalankan kajian tersebut.

Research proposal adalah satu dokumen atau proses yang sangat penting. Ini kerana ia akan memberi satu hala tuju kerana ianya antara dokumen yang pertama yang akan dinilai oleh panel yang pakar dan mendapat maklum balas yang berguna. Dari maklum balas itu, pelajar boleh gunakan untuk menentukan hala tuju kajian.

Nak Contoh Research Proposal

Saya akan kongsikan research proposal saya semasa buat PhD di Universiti Teknologi PETRONAS dahulu. Proposal saya ini diterima dengan baik semasa sesi pembentangan kali pertama. Research proposal saya ini juga telah digunakan sebagai research proposal contoh kepada pelajar-pelajar baharu Universiti Teknologi Petronas semasa kelas research methodology di peringkat universiti.

Dapatkan di sini:  Research Proposal PhD UTP Dr Hariz

Teknik Menulis Research Proposal

Tajuk proposal amatlah penting. Tajuk tersebut mestilah disusun mengikut susunan kepentingan perkataan. Perkataan yang lebih penting mestilah dihadapan. Tajuk yang baik perlulah jelas dan tepat dan merumuskan tentang kajian kita.

Abstrak pula boleh ditulis di peringkat akhir menyediakan proposal.

introduction: Mulakan proposal dengan bahagian “introduction” atau pengenalan. Anda boleh memasukkan gambar-gambar yang penting untuk menjelaskan perkara yang rumit di dalam proposal. Tetapi, jangan terlalu banyak menggunakan gambar. Cukup sekadar yang perlu. introduction perlu menerangkan latar belakang kajian supaya panel-panel dapat memahami kepentingan kajian ini dilakukan.

Literature Review: Bab kedua yang perlu dimuatkan ialah literature literature. Anda perlu menunjukkan bahawa terdapat “gap” atau lompong / jurang pada penyelesaian yang ada sekarang. Tujuan kajian adalah cuba untuk merapatkan lompong / jurang tersebut.  Anda boleh menunjukkan kajian-kajian yang sedia ada melalui jadual perbandingan di akhir bab Literature Review ini.

Research Methodology juga penting untuk menunjukkan bagaimana anda akan melaksanakan kajian tersebut. Ianya ibarat satu pelan ataupun rangka aktiviti-aktiviti yang akan dilaksanakan. Bahagian metodologi ini sangat penting kerana panel ingin melihat adakah kita sudah mempunyai pelan yang betul dan sesuai untuk melaksanakan kajian kita.

Struktur Research Proposal: Bahagian demi Bahagian

Kebanyakan universiti di Malaysia menerima struktur yang hampir sama, walaupun nama bahagian mungkin berbeza sedikit. Jika anda faham fungsi setiap bahagian, anda tidak perlu bergantung sepenuhnya kepada contoh orang lain.

• Tajuk: spesifik, boleh diuji, dan menunjukkan skop kajian. Elakkan tajuk yang terlalu umum seperti “Kajian tentang AI”.
• Pengenalan dan latar belakang: apa isunya, kenapa ia penting sekarang, dan siapa yang terkesan.
• Penyataan masalah: satu perenggan yang menerangkan jurang sebenar, bukan sekadar “kurang kajian dilakukan”.
• Objektif kajian: biasanya tiga hingga lima objektif, setiap satu bermula dengan kata kerja yang boleh diukur.
• Soalan kajian: setiap soalan mesti sepadan dengan satu objektif.
• Sorotan literatur ringkas: tunjukkan anda tahu apa yang sudah dikaji dan di mana jurangnya.
• Metodologi: reka bentuk kajian, populasi dan sampel, instrumen, cara pengumpulan data, dan cara analisis.
• Sumbangan dan kepentingan kajian: kepada teori, amalan, dan dasar.
• Jadual kerja dan rujukan: Gantt chart ringkas dan rujukan mengikut format yang ditetapkan fakulti.

Perbezaan Proposal Master dan Proposal PhD

Ramai pelajar menggunakan contoh proposal master untuk memohon PhD, kemudian ditolak kerana skop tidak mencukupi. Perbezaannya bukan pada panjang, tetapi pada tuntutan keaslian.

• Proposal master selalunya memadai jika anda mengaplikasikan kaedah sedia ada kepada konteks, populasi atau data baharu.
• Proposal PhD perlu menunjukkan sumbangan asli: kaedah baharu, teori baharu, atau penemuan yang mengubah cara sesuatu masalah difahami.
• Panjang tipikal proposal master ialah 10 hingga 20 muka surat, manakala proposal PhD selalunya 20 hingga 40 muka surat, bergantung kepada garis panduan fakulti anda.

Kesilapan Biasa yang Menyebabkan Proposal Ditolak

• Penyataan masalah yang hanya berbunyi “kurang kajian” tanpa bukti daripada literatur.
• Objektif dan soalan kajian yang tidak sepadan antara satu sama lain.
• Metodologi yang tidak menjelaskan bagaimana data akan dianalisis, hanya menyatakan alat yang digunakan.
• Rujukan yang terlalu lama atau tidak konsisten formatnya.
• Skop terlalu besar sehingga mustahil disiapkan dalam tempoh pengajian.

Cara Menggunakan Contoh Proposal dengan Betul

Contoh proposal berguna sebagai rujukan struktur, bukan untuk disalin. Cara paling selamat: baca dua atau tiga contoh dalam bidang anda, senaraikan tajuk bahagian yang mereka guna, kemudian tulis semula sepenuhnya menggunakan kajian dan data anda sendiri. Universiti di Malaysia kini menggunakan perisian semakan persamaan, jadi menyalin struktur ayat adalah risiko yang tidak berbaloi.

Untuk pengurusan rujukan, anda boleh mula dengan panduan cara menggunakan Zotero dengan MS Word dan Google Scholar. Jika kajian anda melibatkan bidang kejuruteraan perisian atau teknologi, rujuk juga panduan systematic literature review dan cara menulis proposal penyelidikan AI.

Soalan Lazim

Apa itu research proposal?

Research proposal ialah dokumen ringkas yang menerangkan apa yang anda ingin kaji, mengapa ia penting, dan bagaimana anda akan menjalankannya. Ia digunakan oleh universiti untuk menilai sama ada kajian anda munasabah dan boleh diselia.

Berapa muka surat proposal yang sesuai?

Sebagai panduan umum, 10 hingga 20 muka surat untuk master dan 20 hingga 40 muka surat untuk PhD. Namun garis panduan fakulti anda sentiasa mengatasi panduan umum ini.

Perlukah saya sudah ada data sebelum menulis proposal?

Tidak. Anda perlu menunjukkan bagaimana data akan diperoleh, bukan menunjukkan data yang sudah dikumpul. Data awal (pilot) boleh menguatkan proposal tetapi bukan syarat.

Bolehkah saya tukar tajuk selepas proposal diluluskan?

Boleh, dan ia perkara biasa. Perubahan kecil pada tajuk atau skop selalunya diterima selagi objektif teras kekal. Perubahan besar biasanya memerlukan kelulusan penyelia dan jawatankuasa pengajian siswazah.

Siapa yang boleh menyemak proposal saya?

Penyelia anda adalah semakan pertama. Selepas itu, minta rakan sekumpulan atau senior membaca bahagian metodologi, kerana bahagian itulah yang paling kerap dikritik semasa pembentangan proposal.

Langkah Seterusnya

Jika anda sedang mencari penyelia atau ingin membincangkan idea kajian dalam bidang kecerdasan buatan dan pengkomputeran, lihat maklumat penyeliaan pascasiswazah atau hubungi saya untuk perbincangan awal.