About MI Write

MI Write is Measurement Incorporated’s automated writing evaluation (AWE) program. AWE programs support the teaching and learning of writing by providing automated scores and feedback to students’ writing. By easing the burden of providing feedback, MI Write allows teachers to assign more writing and focus their feedback efforts. In turn, MI Write affords students the increased writing practice opportunities they need to improve writing quality. Moreover, MI Write’s automated writing quality scores provide timely and reliable assessment data—which can be used to examine changes in performance over time—and automated feedback helps students improve their knowledge of writing quality criteria. MI Write is distinguished by the following features:

 

  • Appropriate for grades 3–12
  • Immediate scores and feedback aligned with Education Northwest’s 6+1 Trait Writing Model
  • Pre-packaged writing prompts—many including stimulus material—for a range of content areas
  • Capabilities for teachers to create and assign custom prompts
  • A library of pre-writing tools to support writing planning
  • Peer review tools
  • Interactive student lessons
  • Usage and performance reports (for students and teachers)
  • Integrated teacher feedback and communication tools
  • Tools to support differentiation (prompt recommendations, grade level scoring options, and personalized feedback)
  • Accessibility resources such as adaptable font size, background color, and highlighting
  • Rostering and class management tools

 

Most importantly, MI Write is supported by an extensive research base. Researchers have examined (1) the efficacy of automated scoring and feedback in improving writing outcomes, (2) the accuracy of automated scoring as a screener for at-risk writers, (3) effects of AWE in naturalistic implementation contexts, and (4) best practices in AWE implementation to improve writing instruction. Links to select peer-reviewed publications are available below.

 

Efficacy of AWE in improving writing outcomes

 

This research uses experimental and quasi-experimental designs to evaluate the efficacy of MI Write in improving writing outcomes.

 

Cruz Cordero, T., Wilson, J., Myers, M., Palermo, C., Eacker, H., Potter, A., & Coles, J. (2023). Writing motivation and ability profiles and transition after a technology-based writing intervention. Frontiers in Psychology—Educational Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1196274

 

Palermo, C., & Thomson, M. M. (2018). Teacher implementation of self-regulated strategy development with an automated writing evaluation system: Effects on the argumentative writing performance of middle school students. Contemporary Educational Psychology, 54, 255–270. https://doi.org/10.1016/j.cedpsych.2018.07.002

 

Wilson, J., & Czik, A. (2016). Automated essay evaluation software in English language arts classrooms: Effects on teacher feedback, student motivation, and writing quality. Computers and Education, 100, 94–109. https://doi.org/10.1016/j.compedu.2016.05.004

 

Wilson, J., & Roscoe, R. D. (2020). Automated writing evaluation and feedback: Multiple metrics of efficacy. Journal of Educational Computing Research, 58(1), 87–125. https://doi.org/10.1177/0735633119830764

 

Writing screening with automated scoring

 

This research examines the viability of MI Write as a screener for at-risk writers.

 

Chen, D., Hebert, M., & Wilson, J. (2022). Examining human and automated ratings of elementary students’ writing quality: A multivariate generalizability theory application. American Educational Research Journal. https://doi.org/10.3102/00028312221106773

 

Wilson, J. (2018). Universal screening with automated essay scoring: Evaluating classification accuracy in Grades 3 and 4. Journal of School Psychology, 68, 19–37. https://doi.org/10.1016/j.jsp.2017.12.005

 

Wilson, J., Chen, D., Sandbank, M. P., & Hebert, M. (2019). Generalizability of automated scores of writing quality in grades 3–5. Journal of Educational Psychology, 111, 619–640. https://doi.apa.org/doi/10.1037/edu0000311

 

Wilson, J., Olinghouse, N. G., McCoach, D. B., Andrada, G. N., & Santangelo, T. (2016). Comparing the accuracy of different scoring methods for identifying sixth graders at risk of failing a state writing assessment. Assessing Writing, 27, 11–23. https://doi.org/10.1016/j.asw.2015.06.003

 

Wilson, J., & Rodrigues, J. (2020). Classification accuracy and efficiency of writing screening using automated essay scoring. Journal of School Psychology, 82, 123–140. https://doi.org/10.1016/j.jsp.2020.08.008

 

Naturalistic implementation contexts

 

This research examines outcomes associated with naturalistic and large-scale implementation of MI Write.

Huang, Y., & Wilson, J. (2021). Using automated feedback to develop writing proficiency. Computers and Composition, 62, 102675. https://doi.org/10.1016/j.compcom.2021.102675

 

Palermo, C., & Thomson, M. M. (2019). Classroom applications of automated writing evaluation: A qualitative examination of automated feedback. In L. Bailey (Ed.), Educational Technology and the New World of Persistent Learning (pp. 145–175). IGI Global. https://doi.org/10.4018/978-1-5225-6361-7.ch008

 

Potter, A., & Wilson, J. (2021). Statewide implementation of automated writing evaluation: Analyzing usage and associations with state test performance in grades 4–11. Educational Technology Research and Development, 69(3), 1557–1578. https://doi.org/10.1007/s11423-021-10004-9

 

Wilson, J. (2017). Associated effects of automated essay evaluation software on growth in writing quality for students with and without disabilities. Reading and Writing, 30, 691–718. https://doi.org/10.1007/s11145-016-9695-z

 

Wilson, J., Ahrendt, C., Fudge, E. A., Raiche, A., Beard, G., & MacArthur, C. (2021). Elementary teachers’ perceptions of automated feedback and automated scoring: Transforming the teaching and learning of writing using automated writing evaluation. Computers & Education, 168, 104208. https://doi.org/10.1016/j.compedu.2021.104208

 

Wilson, J., & Andrada, G. N. (2016). Using automated feedback to improve writing quality: Opportunities and challenges. In Y. Rosen, S. Ferrara, & M. Mosharraf (Eds.), Handbook of research on technology tools for real-world skill development (pp.678–703). IGI Global. https://doi.org/10.4018/978-1-4666-9441-5.ch026

 

Wilson, J., Huang, Y., Palermo, C., Beard, G., & MacArthur, C. A. (2021). Automated feedback and automated scoring in the elementary grades: Usage, attitudes, and associations with writing outcomes in a districtwide implementation of MI Write. International Journal of Artificial Intelligence in Education, 31, 234–276. https://doi.org/10.1007/s40593-020-00236-w

 

Wilson, J., Myers, M. C., & Potter, A. (2022). Investigating the promise of automated writing evaluation for supporting formative writing assessment at scale. Assessment in Education: Principles, Policy & Practice, 29(2), 183–199. https://doi.org/10.1080/0969594X.2022.2025762

 

Wilson, J., Olinghouse N. G., & Andrada, G. N. (2014). Does automated feedback improve writing quality? Learning Disabilities: A Contemporary Journal, 12, 93–118.

 

Best practices in AWE implementation

 

This research investigates how to best implement MI Write to improve writing instruction.

Palermo, C., & Wilson, J. (2020). Implementing automated writing evaluation in different instructional contexts: A mixed-methods study. Journal of Writing Research, 12(1), 63–108. https://doi.org/10.17239/jowr-2020.12.01.04

 

Wilson, J., Potter, A., Cordero, T. C., & Myers, M. C. (2022). Integrating goal-setting and automated feedback to improve writing outcomes: A pilot study. Innovation in Language Learning and Teaching, 1-17. https://doi.org/10.1080/17501229.2022.2077348