Decision letter for "Maximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games"

2020 ◽  
Author(s):  
Valerie Shute ◽  
Seyedahmad Rahimi ◽  
Ginny Smith ◽  
Fengfeng Ke ◽  
Russell Almond ◽  
...  

2020 ◽  
Author(s):  
Valerie Shute ◽  
Seyedahmad Rahimi ◽  
Ginny Smith ◽  
Fengfeng Ke ◽  
Russell Almond ◽  
...  

2020 ◽  
pp. 153450842094193
Author(s):  
Dandan Yang ◽  
Elham Zargar ◽  
Ashley Marie Adams ◽  
Stephanie L. Day ◽  
Carol McDonald Connor

Stealth assessment has been successfully embedded in educational games to measure students’ learning in an unobtrusive and supportive way. This study explored the possibility of applying stealth assessment in a digital reading platform and sought to identify potential in-system indicators of students’ digital learning outcomes. Utilizing the user log data from third- to fifth-grade students ( n = 573) who read an interactive Word Knowledge E-Book, we examined various user log variables and their associations with word knowledge and strategic reading outcomes. Descriptive analysis provided a depiction of the real-time reading processes and behaviors in which students engaged while digitally reading. Multiple regression analysis with classroom fixed effects demonstrated that user log variables relevant to answering questions and making decisions (i.e., percentage of embedded questions answered correctly; number of attempts to answer the questions; and making implausible decisions) were significantly associated with students’ word knowledge and strategic reading outcomes. Variables indicating reading time and frequency, however, were not significantly associated with these outcomes. This study highlights the potential of interactive e-books as another digital learning environment to establish stealth assessment, which may allow researchers and educators to track students’ reading processes and predict reading outcomes while supporting digital learning.


Author(s):  
Valerie Shute ◽  
Seyedahmad Rahimi ◽  
Ginny Smith ◽  
Fengfeng Ke ◽  
Russell Almond ◽  
...  

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