Learn how you can improve your writing process to write academic essays
Sep 25, 2023 |
17 Mins Read
In academia, where ideas and knowledge converge, the written word is a powerful tool for conveying research and arguments. However, the journey from a blank page to a polished essay involves more than inspiration; it demands a systematic and strategic approach. The steps involved in the writing process are considered the building blocks of an essay, the academic writing style itself provides a deep knowledge of the subject matter and helps writers construct evidence-based arguments within their respective fields. This blog post explores the essential steps, techniques, and insights to improve your writing process and gear the approach towards academic essays.
Essay Writing Basics
The purpose of academic essays is to advance ideas and exchange discourse amongst scholars while also teaching the writer to think critically and analyse various areas of research. When structuring and writing an academic essay, it is essential to plan the flow of information to complement one another strategically; the research points contained in each paragraph have to be simple to absorb and not overbearing.
An academic essay has 3 key components: introduction, body paragraph and conclusion.
Pre-Writing Phase
Before writing the essay, having several brainstorming sessions will help writers understand the topic, scope, and arguments within the academic essay. Brainstorming allows writers to build enthusiasm and commitment towards the essay, as the topic becomes clearer with research, discussion and planning. Listed below are a few effective brainstorming techniques:
- Mind Mapping
A mind map is essential for brainstorming as it tracks related concepts. The first step is to write down the larger subject and then write down anything that is relevant to that, this helps writers and researchers visualise all the information related to the topic. It can be used to either break down a larger subject or focus on a certain component of a subject, this is beneficial for academic writers as it helps generate new ideas, foster collaboration and organise information.
- Clustering
The cluster analysis is a great method to club or “cluster” information and data together over certain similarities. This learning technique can be adapted to a brainstorming method to allow academic writers to structure their essays strategically which would allow information and ideas to flow smoothly.
- Free Writing
Free writing is a brainstorming method geared towards writers, it allows writers to write about a topic with no rules, guidelines or structure. The aim is to write as the thoughts come so that the writer can establish how much information they have on a topic. There are 3 simple rules to get this method right: don’t pause to read anything you have written, don’t cross out or erase anything as that is editing and not writing, and finally, don’t worry about spelling or grammar. This method allows writers to generate their ideas and polish them later, rather than having a thought and letting it go.
After having productive brainstorming sessions, the next step is to start the research. Certain institutions have guidelines as to what they consider reputable resources, for example, Wikipedia is not considered an academic source of information as the pages can be edited and written by anyone. Access reputable academic databases and libraries to conduct your research, We have listed a few below:
Once the research phase is done, you will have gathered a good amount of resources and information on your essay topic. The next crucial step is to develop a thesis statement, an essay has to have a thesis statement to serve as a guide for the reader and develop the author’s argument. Furthermore, formulating the thesis statement allows authors to see how their ideas are perceived in a sentence or two. A strong thesis statement specifies one main idea and asserts the author’s conclusions on the essay question or topic.
For example, if your essay is about the implementation of sustainable practices in the transport sector, your thesis statement can be: In recent years, there has been a rise in sustainable initiatives, this essay highlights and argues that sustainability in transportation is beneficial for human advancement and slowing climate change.
Writing The Essay
Once the initial stages of brainstorming, research, and the formulation of a thesis statement are done, the writing process is equipped with a clear roadmap. Each paragraph in an academic essay serves as a building block, cementing the foundation of the thesis while allowing room to explore other perspectives.
- Introduction
The introductory paragraph of an academic essay sets the tone and outlines the map of the essay. It should give the reader a clear idea of the points, arguments and methods the essay will highlight and discuss. There are 4 main components of a good essay introduction paragraph; the hook, context, thesis statement and a clear structure of the essay.
Example: The rise of sustainable practices in the transport sector is imperative to its advancement (Hook). In recent years, the world has witnessed electric cars, alternative routes, carpooling applications, and improvements in public transport; these enhancements have encouraged the general population to utilise alternative methods of transport rather than driving their personal vehicles daily (Context). This essay states that sustainable practices in the transport sector are beneficial for human advancement and slowing climate change (Thesis). The essay discusses the development and implementation of sustainable aviation fuel in recent flights while acknowledging key drawbacks. Furthermore, the essay assesses how carpooling alternatives are valuable for the safety of the environment; and finally, the accessibility and affordability of public transport (Structure).
- Developing Arguments
To effectively develop the arguments that support the thesis statement, the writer should deconstruct the topic and map all possible aspects of the topic. Based on available research, literature and evidence; create a stance that has appropriate citations. Each body paragraph should break down the argument and end with an explanation as to why the essay’s stance is convincing.
- Structuring Body Paragraphs
In an academic essay, each body paragraph is dedicated to a specific point or argument; this paragraph would consist of a topic sentence, evidence, opposing research, context and explanation. Each developed argument should flow and serve the research paper’s positioning in the subject area. The best practice for structuring effective body paragraphs is to follow the P.E.E method which stands for point, evidence and explanation.
Example: The usage of sustainable aviation fuel is key to maintaining the same amount of weekly flights while reducing its effects on climate change (Point). In recent studies, Smith (2021) found that the components required to produce sustainable aviation fuel not only source environmentally friendly ingredients but also practice eco-friendly processes during the production and manufacturing phases (Evidence). The approach to creating sustainability in transport starts by examining the processes by which the vehicles are manufactured as the environmental output of those factories is significant, utilising sustainable aviation fuel eliminates harmful production practices and decreases pollution caused by aeroplanes (Explanation).
- Writing the Conclusion
The conclusion of an academic essay should be an impactful recap of the essay, which should include supporting evidence for the arguments presented; by this paragraph in the essay, the reader should be drawn to supporting the thesis statement.
Editing and Polishing
During the editing stage, it is common for authors to look for grammatical errors; while this is important, it’s also beneficial to keep an eye out for clarity issues. In academic writing, structuring clear and concise sentences is imperative so that all readers can efficiently comprehend the material.
Here is a check-list of what you should look out for while editing an academic essay:
- Correct running sentences with too many subordinate clauses
- Sentences should be written in active voice
- Assess whether a sentence is written in an academic and formal tone
- Assess whether the essay is structured for the intended audience and purpose
Finalising the Essay
Once the essay has reached the finalising phase, it’s important to refer to your institutional formatting guidelines and ensure that all the requirements have been met. Once that is done, the bibliography has to be double-checked to ensure the references are in the correct style without grammar and formatting mistakes. The bibliography is an essential part of an academic essay as it helps readers, professors, and researchers understand where the evidence was retrieved from and how the arguments were constructed; having an accurate bibliography also gives the essay credibility. The final step is to give the essay one last proofread to ensure that it is free of errors.
FAQs
How long should an essay be?
Ideally, an essay should be about 5-7 pages which should contain about 1500-2000 words. However, a detailed essay can range from anywhere between 8-10 pages containing about 2500-3000 words.
What are the key elements of a perfect essay?
Great essays have a clear and concise introduction, thesis and conclusion. The body paragraphs within a good essay flow and connect back to the thesis statement, creating cohesive arguments as the academic paper progresses.
How can I improve my essay-writing skills?
Improving your essay writing skills lies in the planning and proofreading phases rather than the writing itself. Before beginning your essay, plan out the paragraphs, and arguments, and follow the structures to create uniformed paragraphs. In the proofreading stage, keep an eye out for grammatical errors as well as clarity-related errors.
Are there any online resources to assist with essay writing?
The most useful essay-writing tool is Grammarly, it offers multiple suggestions and corrections as you write so that the corrections can be made simultaneously, further simplifying the proofreading stage.
How important is the thesis statement in an essay?
The thesis statement gives the essay direction and provides a clear roadmap to the writer. Every other component of the essay should support or explain the thesis statement.
How do I avoid plagiarism in my essay?
The most effective way to avoid plagiarism is to keep a record of all the sources you will utilise in your essay and then paraphrase the points, you will then have to cite the original author using in-text citations.
From Curator to Digital Navigator: Evolving Roles for Modern Librarians
With the growing integration of digital technologies in academia, librarians are becoming facilitators of discovery. They play a vital role in helping students and researchers find credible information, use digital tools effectively, and develop essential research skills. At Zendy, we believe this shift represents a new chapter for librarians, one where they act as mentors, digital strategists, and AI collaborators. Zendy’s AI-powered research assistant, ZAIA, is one example of how librarians can enhance their work using technology. Librarians can utilise ZAIA to assist users in clarifying research questions, discovering relevant papers more efficiently, and understanding complex academic concepts in simpler terms. This partnership between human expertise and AI efficiency allows librarians to focus more on supporting critical thinking, rather than manual searching. According to our latest survey, AI in Education for Students and Researchers: 2025 Trends and Statistics, over 70% of students now rely on AI for research. Librarians are adapting to this shift by integrating these technologies into their services, offering guidance on ethical AI use, research accuracy, and digital literacy. However, this evolution also comes with challenges. Librarians must ensure users understand how to evaluate AI-generated content, check for biases, and verify sources. The focus is moving beyond access to information, it’s now about ensuring that information is used responsibly and critically. To support this changing role, here are some tools and practices modern librarians can integrate into their workflows: AI-Enhanced DiscoveryUsing tools like ZAIA to help researchers refine queries and find relevant studies faster. Research Data Management Organising, preserving, and curating datasets for long-term academic use. Ethical AI and Digital Literacy Training Teaching researchers how to verify AI outputs, evaluate bias, and maintain academic integrity. Collaborative Digital Spaces Facilitating research communication through online repositories and discussion platforms. In conclusion, librarians today are more than curators, they are digital navigators shaping how knowledge is accessed, evaluated, and shared. As technology continues to evolve, so will its role in guiding researchers and students through the expanding world of digital information. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }
Strategic AI Skills Every Librarian Must Develop
In 2026, librarians who understand how AI works will be better equipped to support students and researchers, organise collections, and help patrons find reliable information faster. Developing a few key AI skills can make everyday tasks easier and open up new ways to serve your community. Why AI Skills Matter for Librarians AI tools that recommend books, manage citations, or answer basic questions are becoming more common. Learning how these tools work helps librarians: Offer smarter, faster search results. Improve cataloguing accuracy. Provide better guidance to researchers and students. Remember, AI isn’t replacing professional judgment; it’s supporting it. Core AI Literacy Foundations Before diving into specific tools, it helps to understand some basic ideas behind AI. Machine Learning Basics:Machine learning means teaching a computer to recognise patterns in data. In a library setting, this could mean analysing borrowing habits to suggest new titles or resources. Natural Language Processing (NLP):NLP is what allows a chatbot or search tool to understand and respond to human language. It’s how virtual assistants can answer questions like “What are some journals about public health policy?” Quick Terms to Know: Algorithm: A set of steps an AI follows to make a decision. Training Data: The information used to “teach” an AI system. Neural Network: A type of computer model inspired by how the brain processes information. Bias: When data or systems produce unfair or unbalanced results. Metadata Enrichment With AI Cataloguing is one of the areas where AI makes a noticeable difference. Automated Tagging: AI tools can read through titles and abstracts to suggest keywords or subject headings. Knowledge Graphs: These connect related materials, for example, linking a book on climate change with recent journal articles on the same topic. Bias Checking: Some systems can flag outdated or biased terminology in subject classifications. Generative Prompt Skills Knowing how to “talk” to AI tools is a skill in itself. The clearer your request, the better the result. Try experimenting with prompts like these: Research Prompt: “List three recent studies on community reading programs and summarise their findings.” Teaching Prompt: “Write a short activity plan for a workshop on evaluating online information sources.” Summary Prompt: “Give me a brief overview of this article’s key arguments and methods.” Adjusting tone or adding detail can change the outcome. It’s about learning how to guide the tool rather than letting it guess. Ethical Data Practices AI tools can be useful, but they also raise questions about privacy and fairness. Librarians have always cared deeply about protecting patron information, and that remains true with AI. Keep personal data anonymous wherever possible. Review AI outputs for signs of bias or misinformation. Encourage clear policies around how data is stored and used. Ethical AI is part of a librarian’s duty to maintain trust and fairness. Automating Everyday Tasks AI can take over some of the small, routine jobs that fill up a librarian’s day. Circulation: Systems can send overdue reminders automatically or manage renewals. Chatbots: Basic questions like “What are the library hours?” can be handled instantly. Collection Management: AI can spot patterns in borrowing data to suggest which books to keep, reorder, or retire. Building Your Learning Path Getting comfortable with AI doesn’t have to mean earning a new degree. Start small: Take short online courses or micro-certifications in AI literacy. Join librarian groups or online forums where people share practical tips. Block out one hour a week to try out a new tool or attend a webinar. A little consistent learning goes a long way. Making AI Affordable Many smaller libraries worry about cost, but not every tool is expensive. Free Tools: Some open-access AI platforms, like Zendy, offer affordable access to research databases and AI-powered features. Shared Purchases: Partnering with other libraries to share licenses can cut costs. Cloud Services: Pay-as-you-go plans mean you only pay for what you actually use. There’s usually a way to experiment with AI without stretching the budget. Showing Impact Once AI tools are in use, it’s important to show their value. Track things like: Time saved on cataloguing or circulation tasks. Patron feedback on new services. How often are AI tools used compared to manual systems? Numbers matter, but so do stories. Sharing examples, like a student who found research faster thanks to a new search feature, can make your case even stronger. And remember, the future of librarianship is about using AI tools in libraries thoughtfully to keep libraries relevant, reliable, and welcoming spaces for everyone. .wp-block-image img { max-width: 75% !important; margin-left: auto !important; margin-right: auto !important; }
Key Considerations for Training Library Teams on New Research Technologies
The integration of Generative AI into academic life appears to be a significant moment for university libraries. As trusted guides in the information ecosystem, librarians are positioned to help researchers explore this new terrain, but this transition requires developing a fresh set of skills. Training your library team on AI-powered research tools could move beyond technical instruction to focus on critical thinking, ethical understanding, and human judgment. Here is a proposed framework for a training program, organised by the new competencies your team might need to explore. Foundational: Understanding Access and Use This initial module establishes a baseline understanding of the technology itself. Accessing the Platform: Teach the technical steps for using the institution's approved AI tools, including authentication, subscription models, and any specific interfaces (e.g., vendor-integrated AI features in academic databases, institutional LLMs, etc.). Core Mechanics: Explain what a Generative AI platform (like a Large Language Model) is and, crucially, what it is not. Cover foundational concepts like: Training Data: Familiarise staff with how to access the institution’s chosen AI tools, noting any specific authentication requirements or limitations tied to vendor-integrated AI features in academic databases. Prompting Basics: Introduce basic prompt engineering, the art of crafting effective, clear queries to get useful outputs. Hallucinations: Directly address the concept of "hallucinations," or factually incorrect/fabricated outputs and citations, and emphasise the need for human verification. Conceptual: Critical Evaluation and Information Management This module focuses on the librarian's core competency: evaluating information in a new context. Locating and Organising: Train staff on how to use AI tools for practical, time-saving tasks, such as: Generating keywords for better traditional database searches. Summarising long articles to quickly grasp the core argument. Identifying common themes across a set of resources. Evaluating Information: This is perhaps the most critical skill. Teach a new layer of critical information literacy: Source Verification: Always cross-check AI-generated citations, summaries, and facts against reliable, academic sources (library databases, peer-reviewed journals). Bias Identification: Examine AI outputs for subtle biases, especially those related to algorithmic bias in the training data, and discuss how to mitigate this when consulting with researchers. Using and Repurposing: Demonstrate how AI-generated material should be treated—as a raw output that must be heavily edited, critiqued, and cited, not as a final product. Social: Communicating with AI as an Interlocutor The quality of AI output is often dependent on the user’s conversational ability. This module suggests treating the AI platform as a possible partner in a dialogue. Advanced Prompt Engineering: Move beyond basic queries to teach techniques for generating nuanced, high-quality results: Assigning the AI a role (such as a 'sceptical editor' or 'historical analyst') to potentially shape a more nuanced response. Practising iterative conversation, where librarians refine an output by providing feedback and further instructions, treating the interaction as an ongoing intellectual exchange. Shared Understanding: Practise using the platform to help users frame their research questions more effectively. Librarians can guide researchers in using the AI to clarify a vague topic or map out a conceptual framework, turning the tool into a catalyst for deeper thought rather than a final answer generator. Socio-Emotional Awareness: Recognising Impact and Building Confidence This module addresses the human factor, building resilience and confidence Recognising the Impact of Emotions: Acknowledge the possibility of emotional responses, such as uncertainty about shifting professional roles or discomfort with rapid technological change, and facilitate a safe space for dialogue. Knowing Strengths and Weaknesses: Reinforce the unique, human-centric value of the librarian: critical thinking, contextualising information, ethical judgment, and deep disciplinary knowledge, skills that AI cannot replicate. The AI could be seen as a means to automate lower-level tasks, allowing librarians to focus on high-value consultation. Developing Confidence: Implement hands-on, low-stakes practice sessions using real-world research scenarios. Confidence grows from successful interaction, not just theoretical knowledge. Encourage experimentation and a "fail-forward" mentality. Ethical: Acting Ethically as a Digital Citizen Ethical use is the cornerstone of responsible AI adoption in academia. Librarians must be the primary educators on responsible usage. Transparency and Disclosure: Discuss the importance of transparency when utilizing AI. Review institutional and journal guidelines that may require students and faculty to disclose how and when AI was used in their work, and offer guidance on how to properly cite these tools. Data Privacy and Security: Review the potential risks associated with uploading unpublished, proprietary, or personally identifiable information (PII) to public AI services. Establish and enforce clear library policies on what data should never be shared with external tools. Copyright and Intellectual Property (IP): Discuss the murky legal landscape of AI-generated content and IP. Emphasise that AI models are often trained on copyrighted material and that users are responsible for ensuring their outputs do not infringe on existing copyrights. Advocate for using library-licensed, trusted-source AI tools whenever possible. Combating Misinformation: Position the librarian as the essential arbiter against the spread of AI-generated misinformation. Training should include spotting common AI red flags, teaching users how to think sceptically, and promoting the library’s curated, authoritative resources as the gold standard. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }
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