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What Computing Can and Could Do…

Computers have changed writing education, but many writing teachers wonder if technology is now turning into a threat. Too many politicians, administrators, and non-profit foundations are rushing to embrace technologies such as MOOCs and adaptive tutoring without skepticism. What is the balance between too little and too much faith in technology?

The question of what computing technology can and cannot do for writing students is something we need to consider — as well as whether or not some of these tasks should be done (by a computer or a human).

1) Formatting. I cannot remember the intricacies of APA or MLA, so I use Bookends with my writing tools. Even Word has improved its basic bibliography formatter to the point I catch few minor errors when I triple check the entries.

Yes, I do tell my students to double and triple check citations and bibliographies, but I also demonstrate Bookends, EndNote, RefWords, and Word's built-in tools. The time saved lets a writer focus on content. We claim ideas matter more than formatting, but we also know editors will reject a paper with sloppy formatting.

2) Grammar, spelling, and mechanics. The quality of automated writing tools has improved dramatically in the last 30 years. I use Grammarian Pro on the Mac and love it. Again, we know the tools are imperfect, but to assume they might never be better than I am would be presumptuous. How often do you receive a document that a basic spelling and grammar check would have improved?

Anyone else use dictation software? The software is getting great at determining "too, to, two" and even using "who" and "whom" properly. My software speaks up and says, "Grammar error." That's either annoying or impressive, but it certainly improves my writing.

3) Fact checking. Yes, there are research projects that demonstrate "fact checks" of papers. Imagine going line-by-line through papers and marking the contents as fact, disputed fact, incorrect fact, or opinion. The technology exists for software to do this very task. Already, law firms use computers to expedite discovery research.
The Truth Teller prototype was built and runs with a combination of several technologies - some new, some very familiar. We've combined video and audio extraction with a speech-to-text technology to search a database of facts and fact checks. The Post also worked with Dan Schultz, creator of Truth Goggles, as he helped consult and shared his knowledge of real-time fact checking. We are effectively taking in video, converting the audio to text, matching that text to our database, and then displaying, in real time, what's true and what's false. The key to the project's success is building an authoritative database - our goal is to identify falsehoods, not create more of them.

<technical_details>

We are transcribing videos using Microsoft Audio Video indexing service (MAVIS) technology. MAVIS is a Windows Azure application which uses Deep Neural Net (DNN) based speech recognition technology to convert audio signals into words. Using this service, we are extracting audio from videos and saving the information in our Lucene search index as a transcript. We are then looking for the facts in the transcription. Finding distinct phrases to match is difficult. Instead, we are focusing on patterns.

We are using approximate string matching, or a fuzzy string searching algorithm. We are implemented a modified version Rabin-Karp using Levenshtein distance algorithm. This will be modified to recognize paraphrasing and negative connotations in the future.
http://www.knightfoundation.org/blogs/knightblog/2013/1/29/debuting-truth-teller-washington-post-real-time-lie-detection-service-your-service-not-quite-yet/
4) Plagiarism detection. Several services already exist that compare submitted papers to a database of existing works. No human could compare every line of a document to other documents. If a paper is factually correct, it can still be a "borrowed" work that doesn't deserve a passing grade.

TurnItIn and other plagiarism detectors are imperfect, but the more data they receive the better they will be at detection. False positives are also a problem, because students stumble with citation formats. Ideally, the plagiarism detectors will improve enough to recognize when a student was trying to cite a source. Honest errors in formatting might also be reduced with formatting tools mentioned earlier.

5) Grading. Okay, robo-grading scares teachers. You can find a lot of articles and essays on this technology. Someday, the technology will work — at least well enough for a first-pass. The reality is, bad writing probably can be detected by software. A human should always verify the results of computer-based grading tools, yet the tools can save time.

I use basic grading tools to recognize common problems. The software is okay, and saves me several hours. As long as we recognize what software can and cannot do as a "robo-grader" we can refine our own processes.

Combine a "truth detector" with plagiarism software and e-grading applications… we start to approach an evaluator of at least acceptable competence.

Technology isn't going to replace the writing teacher, but it certainly will help us a lot.

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