Key Takeaway: Currently, there are many sound, evidence-based reading comprehension interventions. However, not all students will demonstrate an adequate response to these interventions. Therefore, as special educators, we need to be aware of how and why students respond to reading comprehension interventions and how attention affects reading comprehension. —Michael Ho

In their study, Amanda Martinez-Lincoln, Marcia A. Barnes, and Nathan H. Clemens (2021) used moderation analysis to investigate for whom and under what conditions reading comprehension interventions are most effective. The authors investigated the following research question: Do language status and pre-intervention levels of anxiety, mind-wandering, and mindset influence the effects of a computer-delivered or teacher-delivered inferential reading comprehension intervention in struggling middle school readers?

The study aimed to:

1) Determine whether students’ mind-wandering, anxiety, and language status were associated with a differential response to an inferential reading comprehension intervention among struggling middle school readers

2) Examine whether these effects varied across instructional delivery systems: teacher-led instruction, computer-led instruction, and a control group (program based on what struggling middle school readers typically receive)

Here are the major takeaways from the article:

• Inference-making, the ability to infer information that is not explicitly stated in the text, is a vital component to reading comprehension. Difficulties in making inferences to connect parts of the text¹ and to associate texts with background knowledge² have been linked to poor reading comprehension. 

• Attention is a core component of engagement and is crucial to academic achievement, including reading comprehension. Martinez-Lincoln et al.  (2021) refer to the 2016 study of Rabiner et al.³ and emphasize that “poor attention can negatively influence students’ long-term academic outcomes in reading and math and can increase risk for not graduating from high school.”

• The purpose of this study was to test the effects of three factors of attention—Mind-Wandering, Anxiety, and Mindset—across three instructional delivery systems in reading: Teacher-led Instruction, Computer-led Instruction, and a Control Group.

• In the study, 67 students in Grade 6 to 8 from three middle schools in the southwest USA were included. A stratified randomized procedure was implemented and students were assigned to one of the three groups: Teacher-led Instruction, Computer-led Instruction, and a Control Group.

• Measures in reading assessment included Test of Word Reading Efficiency 2nd ed., Sight Word Efficiency, Connect-IT Inferential Reading Comprehension Assessment, Bridging Inference Task, and the Wechsler Individual Achievement Test 3rd ed., Reading Comprehension. Measures in attention included Mind-Wandering Questionnaire, Multidimensional Anxiety Scale for Children 2nd Edition, and Mindset Survey.

• Among students with similar high levels of mind-wandering, students in the computer-delivered intervention were able to make better inferences on the Bridge-IT Near task, a part of the Bridging Inference Task. Mind-wandering did not have an effect in the teacher-led intervention; this may be due to verbal praise and encouragement reducing the influence of mind-wandering in this group.

• Compared to similarly anxious peers in the control group, Martinez-Lincoln et al., (2021) found that “students in the computer-led intervention performed better on a comprehension test that required them to make several different types of inferences.” It is important to note that higher levels of anxiety were positively correlated with higher levels of reported mind-wandering.

• The effects of mindset on inferential reading comprehension intervention were found to be similar. This could be due to the small sample size or to the general mindset measures not being as sensitive as reading-specific mindset measures.

• Martinez-Lincoln et al. (2021) found that English Learners (ELs) “scored lower overall than non-ELs on all reading measures.” ELs scored higher in the control group compared to ELs in the computer-led instruction. More notably, in the teacher-led instruction, the ELs’ performance did not significantly differ from those of non-ELs. This may be due to more in-depth feedback and additional examples provided in the teacher-led instruction.

• This study had some limitations, such that the sample size was relatively small and that it was not realistic to include and control all of the factors that may influence students’ responses to reading instruction. In addition, participants read and answered the student engagement questionnaires silently. Although an interventionist was present, it is possible that a student may have misread or misunderstood the statements in the questionnaire. Finally, not all students were receiving reading instruction in the control group. 

• The inclusion of student characteristics and instructional elements, such as group size and delivery by a computer or a teacher, in future research may be essential for developing effective reading comprehension instruction for struggling middle school readers, especially those who are ELs, have high levels of mind-wandering, or have high levels of anxiety.

Summarized Article:

Martinez-Lincoln, A., Barnes, M.A. & Clemens, N.H. Correction to: Differential Effectiveness of an Inferential Reading Comprehension Intervention for Struggling Middle School Readers in Relation to Mind-wandering, Anxiety, Mindset, and English Learner Status. Ann. of Dyslexia 71, 346 (2021). https://doi.org/10.1007/s11881-021-00215-3

Summary by: Michael Ho—Michael supports the MARIO Framework because it empowers learners to take full control of their personalized learning journey, ensuring an impactful and meaningful experience.

_{Additional References:}

1. _{Cain, K., & Oakhill, J. V. (1999). Inference making ability and its relation to comprehension failure in young children. Reading and Writing, 11, 489–503. https://doi.org/10.1023/A:1008084120205.}
2. _{Cain, K., Oakhill, J. V., Barnes, M. A., & Bryant, P. E. (2001). Comprehension skill, inference-making ability, and their relation to knowledge. Memory & Cognition, 29, 850–859. https://doi.org/10.3758/BF03196414.}
3. _{Rabiner, D. L., Godwin, J., & Dodge, K. A. (2016). Predicting academic achievement and attainment: the contribution of early academic skills, attention difficulties, and social competence. School Psychology Review, 45, 250–267. https://doi.org/10.17105/SPR45-2.250-267.}