Literacy and mathematics have been shown to be related to each other across languages, ages, and levels of proficiency (e.g., [5, 11, 6, 19, 29, 35, 39, 43, 46, 49, 53, 57]). More specifically, math instruction is further complicated and becomes more difficult when occurring in a non-native language of instruction (e.g., [2, 8, 16, 18, 20, 31, 41, 50]). In this paper, we perform a linear mixed-effects regression analysis on large-scale institutional student data to test the impact of a non-native, and in some cases - new, language of instruction on students' success as measured by course grades. Specifically, we compare the relationship between achievement in math and English classes for Chinese international students (who previously received math instruction in Chinese dialects), relative to Indian international students (who previously received math instruction in English), relative to a baseline of American students of varying ethnic backgrounds, who have previously received math instruction in English, and for many of whom it is a native language. Findings show that language barriers do not impede international students' math achievement. Future work should further characterize the factors that contribute to students' math achievement, overcoming any limitations that may be posed by language barriers.

Reading comprehension is essential for students' ability to build knowledge. Students' comprehension abilities can be enhanced by providing students with deliberate practice and formative feedback on reading comprehension strategies. iSTART is an Intelligent Tutoring System (ITS) that is designed to provide instruction in reading strategies with minimal teacher supervision - affording the ability to teach reading strategies at scale. In the current study, undergraduate students received reading strategy instruction and opportunities for deliberate practice via the iSTART intelligent tutoring system or not (i.e., no-treatment control group). Participants' reading comprehension and psychology knowledge were assessed. The iSTART group demonstrated substantially greater scores than the control group on a post-training reading comprehension measure (Cohen's d > 1.0). The average psychology knowledge scores did not differ between iSTART (post-training) and control groups, but overall these scores were unexpectedly low. Within the iSTART group, there was no difference in reading comprehension and knowledge scores as a function of students' different behaviors in the system. Overall, the results indicate that iSTART is an effective tool to teach reading strategies at large scale. However, further work is required to test the extent to which iSTART supports knowledge building.

The Interactive Strategy Training for Active Reading and Thinking (iSTART) game-based intelligent tutoring system (ITS) was developed with a foundation of comprehension theory and principles of learning science to improve students’ comprehension of complex scientific texts. iSTART has been shown to improve reading comprehension for learners from middle school through adulthood, particularly lower knowledge readers, through strategy instruction and game-based practice. This paper describes iSTART, the theoretical foundations that have guided iSTART development, and evidence for the feasibility of game-based practice to improve learning outcomes. This paper also introduces a novel method of assessing students’ reading comprehension through game-based literacy assessments that have been incorporated in iSTART. The development of these stealth assessments was guided by recent work emphasizing the need for rapid, dynamic, and low stakes assessments that evaluate students’ reading skills in the context of brief, dynamic games. Stealth assessments can generate estimates of multiple aspects of students’ reading comprehension quickly and within a motivating environment. The work described in this paper is a promising method to assess students’ literacy in an unobtrusive and authentic way that may lead to improved learning outcomes for students.