Academic Language
What is Academic Language?
Academic language is the writing, speaking, and reading we use in academic settings. It is not defined by set grammatical rules, vocabulary, formatting, or style. Instead, academic language has been established by social norms in academic settings around what language should look and sound like, which is not always consistent, unbiased, or easily explained. This resource shares general guidance on using academic language in your writing while incorporating your own voice and style.
Why do we use academic language in writing?
Sharing information widely and accessibly: Academic language is intended to set guidelines around communication in academia. These guidelines offer us the opportunity to make our ideas understandable and accessible to more people. By using language that is understood by your audience, organization that makes your ideas easy to follow, and consistent grammar and style, your reader can focus on what you are saying, rather than how you are saying it.
Communicating complex ideas: Academic language often focuses on complex topics, shares new ideas, and synthesizes large amounts of research and information. Following guidelines to make our writing more consistent and accessible also makes these complex ideas clear to others.
General Principles
Write clearly, concisely, and consistently: Academic language is often complex and technical, but sentences that use fewer words and connect ideas together clearly make it easier for your reader to understand your message. Being concise ensures that the focus of your writing is on your ideas. Using active voice, reducing prepositional phrases and redundancy, and being intentional about your word choice helps make writing more concise. See our handout on concise writing. Consistent writing is developed as you hone your own style and approach to writing, but is greatly benefitted by following a style guide, such as APA, MLA, or others more relevant to your topic or field.
Write to your intended audience: Knowing who will be reading your writing–and what terminology, phrasing, and ideas they will understand–will help you write academically. Writing for a peer in a course will require more explanation, discussion of background information, and clearer transitions than would be required when your audience is your professor, who has a more comprehensive understanding of your topic. Before writing, and in your revision process, make sure to factor in your audience. See our handout on writing for your audience.
Show what you know: Your ability to both share information you have learned and contribute new ideas to the subject area in which you are writing is at the core of academic language. Demonstrating your understanding and ideas through a clear thesis and logical organization that builds upon previous information, and supporting your claims and arguments with evidence shows your engagement with the material and creates opportunity for you to join academic discussion on the topic.
Identity and Voice Matter
Academic language should make your writing clearer, more organized, and more accessible to your reader, not make you sound like AI. If your writing no longer sounds like something you would say, feels dry or uninteresting, or does not communicate ideas in a way that is authentic to you, consider what ideas, sentence structures, punctuation, word choices, and organization makes your writing authentic to your voice. Then, take the time to revise your work and reintroduce your personal style and identity to the writing.
| Excerpt from Deep learning: | Principles in Practice | Discussion |
| “Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction1,2. These methods have dramatically5 improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics1,2,4. Deep learning discovers intricate structure5 in large data sets by using the backpropagation algorithm3 to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer1,2. Deep convolutional nets3 have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light5 on sequential data such as text and speech1,2,4.” | Clear Communication | Clarity is not a single, identifiable feature, but rather an amalgamation of the major hallmarks of academic communication. Consider each of the sentences marked with a superscript and how the features highlighted add to clarity. |
| Knowledge Shared | The writers effectively communicate their topic and background information, but the purpose of this article (a review of the topic and literature surrounding it) is not clear until well into the body. While this is acceptable in a journal where the purpose of the writing is made clear through a section heading, in many cases this needs to be explicitly stated in the abstract. | |
| 1Consistent Organization | Despite its brevity, the writers still prioritized a clear organization: introduction to the topic and its importance, background information, and new research. | |
| 2Concise Writing | The use of clear, short, direct sentences makes the abstract concise. There is no unnecessary information, but this abstract may be too concise for some readers, as the purpose is missing and some sentences are quite dense with information. | |
| 3Audience and Topic-Specific Language | This paper was published in Nature, a well-regarded science journal, whose readers can span a broad array of disciplines. This abstract uses topic-specific terms to computer science such as “backpropagation algorithm” and “convolutional nets” that may not be understood by all readers, but can be inferred and understood by reading further. | |
| 4Precise Language Choices | While an abstract of a review necessitates some generalization, the writers are precise in their descriptions of deep learning processes and comprehensive in their listing of items affected by deep learning. | |
| 5Writer Voice | The very direct, concise style of writing is favored by some academic disciplines, and likely by these writers as well. In addition to this, there are stylistic word and phrase choices throughout. |
LeCun, Y., Bengio, Y., Hinton, G. (2015). Deep learning. Nature, 521 (7553), pp.436-444. 10.1038/nature14539. .
By Laura Widman, Writing Center Assistant Director
Copyright 2024
Nesbitt-Johnston Writing Center, 91制片厂
Hamilton.edu/writing
