DECODING
Auto Summary
Overview
Auto summary tools allow you to take a passage and automatically summarize it into key points; shortening the passage while keeping meaning.
Auto summary can be installed or downloaded on mobile devices and typically does not require an internet connection.
Auto Summary can support students with difficulties with reading comprehension or the brainstorming stage of the writing process.
To see Auto Summary in action, check out this video: https://www.youtube.com/watch?v=hmRj65T17JM
Research
Yang et al (2013)
Yang and colleagues tested 25 participants who were given passages to study. The participants had no background knowledge on these topics. Some participants had the original passage (1500 words), while others had various length (400, 250, 100 words) auto summarized passages.
The participants with auto summary passages made more mistakes, but also completed their test in significantly less time. Participants with 400 word summaries, or 30% of the passage, made 10% more mistakes than the full passage group, but were just over twice as fast. The smaller summaries led to more mistakes and faster responses. Because of this, it is recommended to have auto summaries of approximately 30% of the total text size in order to maximize efficiency while not greatly sacrificing accuracy.
Edyburn (2002)
A case study by Edyburn followed a single student with academic difficulties and poor reading and writing. This student was training on how to use auto summary and asked to complete a research task.
The student’s writing grade improved from a C+ to an A, and the length of the student’s passages increased from 80 word assignments to 180 word assignments. Therefore, it seems that auto summary tools can be used to support reading comprehension skills.
Ghambir & Gupta (2016)
This survey examined text summarization techniques used in the past decade.
The authors conclude that extractive methods (pulling exact sentences and phrases) should be preferred over abstractive (reconstructing) until better software develops.
Research Quick Facts
Advantages
Almost no learning curve; users need only to copy and paste information
Effectively reduces size of documents while preserving meaning, which can reduce information processing load
Can be mounted onto mobile devices
Significantly faster than summarizing by hand
Disadvantages
Some information is lost in the auto summary process and no system will ever be perfect
Has been shown to increase errors when used to study for tests
Requires information in electronic text form
To Consider
Summarization “by hand” or summarization done by the reader has shown to be an excellent study tool that significantly increases comprehension and test scores on related content (Friend, 2000). Part of these effects have been shown to be the act of creating the summary is what improves retention, meaning using auto summary does not have the same effects. As such, Auto Summary is best used when there is an excess of information that needs to be reduced.
Insights from Practice
Reading
Auto summary, especially those utilizing AI, can help students in multiple ways:
1) Help students be less overwhelmed with the length of a reading,
2) Can help with pre-reading, by first reading a summary it can prime the reader to the content of the text and activate prior knowledge, and
3) For people with intellectual disabilities or reading comprehension deficits auto-summary could be used in an ongoing basis to reduce complexity and help extract key ideas.
Writing
When collecting research for writing, auto summarization can assist with screening an article to see if it is worthwhile to read in full. AI can do this well using a prompt such as "Simulate an expert teacher who is going to read the below passage and complete a summary of 250 words max for their student".

Product | Price | OS Compatibility | Internet Reliance |
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Exact prices change frequently, which is why only approximate ranges are listed.
$ - Under $5
$$ - Between $6 and $50
$$$ - Between $51 and $250
$$$$ - Over $250
References
Edyburn, D. (2002). Research and Practice. Journal of Special Education Technology, 17(4). 53-60.
Gambhir, M., & Gupta, V. (2016). Recent automatic text summarization techniques: A survey. Artificial Intelligence Review, 47(1), 1-66. doi:10.1007/s10462-016-9475-9
Huang L, He Y, Wei F, Li W (2010) Modeling document summarization as multi-objective optimization. In: Proceedings of the third international symposium on intelligent information technology and security informatics, pp 382–386
Friend, R. (2000). Teaching Summarization as a Content Area Reading Strategy. Journal of Adolescent & Adult Literacy, 44(4), 320-329.
R.J. Marzano, D.J. Pickering, J.E. Pollock. Classroom instruction that works: Research-based strategies for increasing student achievement. (2nd ed.), ASCD, Alexandria, VA (2001)
Yang, C. C., & Wang, F. L. (2008). Hierarchical summarization of large documents. Journal of the American Society for Information Science and Technology, 59(6), 887-902. doi:10.1002/asi.20781