Script
Slide 1
The following is a slidecast of an analytical review of the literature on reading comprehension in technology-based learning.
Slide 2
Reading comprehension has been identified as one of the key factors that affects learners’ overall ability and success in school (Ertem, 2010).
In recent years there has been a growing concern that students are not meeting expectations in this area (McNamara et al., 2006).
Technology-based learning environments offer promising interventions to improve reading comprehension skills (Rodriguez et al., 2012).
They also provide opportunities to increase areas of motivation, interest and engagement, which directly impact reading comprehension (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Murphy, 2007; Roberts & Barber, 2013; Rodriguez et al., 2012).
Slide 3
Methods (no voice over)
Slide 4
This analysis included 15 studies from the years 2004 to 2014 (Roberts & Barber, 2004; Ponce et al., 2013).
The analysis only considered sources with the words reading comprehension as part of their title.
The studies were selected from 12 educational technology journals.
They all included an electronic medium. These media included electronic texts on mobile devices or computers, or educational computer software.
The number of participants in the studies ranged from 28 to 2468.
The analysis excluded meta-analyses and book reviews.
Slide 5
Data collection involved seven studies that were designed to compare text formats. Electronic texts included text on computer, Kindle 3, iPad, CD ROM or Nook (Roberts & Barber, 2013; Ertem, 2010; Fry & Gosky, 2007/2008, Grimshaw et al., 2012; Schugar et al., 2011).
The remaining eight studies tested software programs that were designed by the researchers, purchased, or free online (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al, 2012; Ponce et al., 2013; Rodriguez et al., 2012; Tozcu & Coady, 2004). These programs were designed to improve literacy or reading comprehension.
The participants in the studies were all students in grade one to university.
They were from mainstream and non-mainstream backgrounds.
Participants were studying ESL, language, language arts, science or social studies.
Slide 6
Findings (no voice over)
Slide 7
The literature analysis revealed four categories related to reading comprehension. These were text format, software design, motivation, interest and engagement, and training, support, and resources.
Slide 8
Text Format (no voice over)
Slide 9
The analysis of the literature revealed that reading instruction in technology-based learning resulted in the same reading comprehension gains, regardless of text format (Connell et al,. 2012; Schugar et al., 2011). Only proficient readers performed better with a print text (Roberts & Barber, 2013).
However, it also resulted in significant improvements in reading comprehension using electronic text with animation (Ertem, 2010), narration (Grimshaw et al., 2007) and/or a pop-up dictionary (Fry & Gosky, 2007/2008; Grimshaw et al., 2007).
Reading instruction in technology-based learning environments also resulted in significant improvements for advanced readers who used text with no additional functions (Roberts & Barber, 2013).
Significant improvements for students with low sustained-attention ability were found when students used electronic text with hypertext that had navigation overviews (Salmeron & Garcia, 2012).
Slide 10
Software Design (no voice over)
Slide 11
The analysis revealed that software design that contributed to increased reading comprehension contained specific instruction to support reading comprehension (Ponce et al., 2013) use of graphic organizers (Ponce et al., 2012), elaborative feedback (Murphy, 2007), literacy skills (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu & Coady, 2004) or self-regulation (Lysenko & Abrami, 2014).
In the studies, software that contributed to increased reading comprehension combined its use with prior knowledge of reading strategies (McNamara et al., 2006), independent silent reading (Cuevas et al., 2012) or partner groups (Murphy, 2007).
In one study the use of two software programs combined resulted in significant gains in reading comprehension (Lysenko & Abrami, 2014).
Slide 12
Motivation, Interest, Engagement (no voice over)
Slide 13
In most of the studies, technology-based learning contributed to increased motivation (Cuevas et al., 2012), interest (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Roberts & Barber, 2013; Rodriguez et al., 2012) and/or engagement (Murphy, 2007). Increasing areas of motivation, interest, and engagement positively impacts reading comprehension.
Only Roberts & Barber (2013) found that some grade two participants, the advanced readers, did not demonstrate consistent reading enjoyment with electronic texts. However, their proficient readers demonstrated consistent reading enjoyment.
Slide 14
Training Support, Resources (no voice over)
Slide 15
The analysis revealed that successful implementation of technology-based learning in the classroom required access to teacher support to increase comfort with using computers and to resolve technical issues (Ponce et al., 2012; Ponce et al., 2013).
Another area of need was teacher and student training in how to use computers and software program features (Connell et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Ponce et al., 2013; Schugar et al., 2011). The authors also suggested that training in electronic media may have positively changed the results of their studies.
Computer resources such as the availability of labs was also an issue that was discussed in several studies (Cuevas et al., 2012; Fry & Gosky).
Slide 16
Discussion (no voice over)
Slide 17
The literature analysis presented evidence to demonstrate that reading comprehension is unaffected by text format (Connell et al., 2012; Schugar et al., 2011).
However, reading comprehension was significantly increased with the use of electronic text with narration (Grimshaw et al., 2007), animation (Ertem, 2010) and/or a pop-up dictionary (Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Schugar et al., 2011).
Reading comprehension was also consistently increased using an electronic text with no additional features for advanced readers (Roberts & Barber, 2013) and with navigation overviews for students with low sustained-attention abilities (Salmeron & Garcia, 2012).
Reading comprehension was consistently increased using computer software designed to teach reading comprehension or literacy skills when combined with regular classroom instruction (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Slide 18
Students and teachers should be comfortable using computers to yield significant gains in reading comprehension in technology-based learning environments (Connell et al., 2012, Grimshaw et al., 2007; McNamara et al., 2006; Ponce et al., 2013; Schugar et al., 2011).
They need consistent experiences with software to net maximum benefits in reading comprehension (Ponce et al., 2013; Rodriguez et al., 2012).
Students and teachers need to be familiar with features of devices for maximum gains in reading comprehension (Connell et al., 2012; Schugar et al., 2011).
Slide 19
Conclusion (no voice over)
Slide 20
The findings of almost all of the studies suggested that reading comprehension is unaffected or increased by electronic text formats (Connell et al., 2012; Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Schugar et al., 2011).
Only Roberts & Barber (2013) found that proficient readers performed better with a print text.
If the electronic text included navigation overviews, narration, dictionary or animation, its use promoted significant reading comprehension gains (Salmeron & Garcia, 2012; Grimshaw et al., 2007, Fry & Gosky, 2007/2008; Ertem, 2010).
Reading comprehension in technology-based learning can be augmented through increased motivation, interest and engagement resulting from technology-based learning environments (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Roberts & Barber, 2013; Rodriguez et al., 2012; Murphy, 2007).
Reading comprehension was increased, with the use of technology-based software designed to promote language development or reading comprehension (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Slide 21
Implications (no voice over)
Slide 22
As studies show that using technology based learning results in significant gains for students, teachers can be assured that in many environments or contexts, technology-based learning will effectively promote reading comprehension gains.
Teachers can use electronic texts with narration, animation, hypertext with navigation overviews and/or a pop-up dictionary to increase students’ reading comprehension (Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007).
They can consistently use computer software combined with regular classroom instruction as a means to increase reading comprehension of all students in their classroom (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Researchers can conduct longer study intervention periods which may further impact reading comprehension (Cuevas et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu & Coady, 2004).
They can also investigate the effects that technology-based learning environments have on motivation, interest and engagement, which in turn will positively impact reading comprehension (Cuevas et al., 2012; Ertem, 2010, Grimshaw et al., 2007; Murphy, 2007; Roberts & Barber, 2013; Rodriguez et al., 2012).
Slide 23
Limitations (no voice over)
Slide 24
This analysis included studies with two distinct purposes – to compare text formats (Connell et al., 2012; Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Roberts & Barber, 2013; Salmeron & Garcia, 2012; Schugar et al., 2011) and to study software programs designed to increase reading comprehension and/or literacy skills (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004). The analysis would have been more comprehensive if it focused on one of these major areas.
The results may have differed if the studies controlled for age, general ability or computer ability of the participants.
Many of the studies were conducted over a short period of time. Results may have differed if the studies were longitudinal (Cuevas et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu &Coady, 2004).
The studies may have also differed if they included larger sample sizes (Rodriguez et al., 2012; Schugar et al., 2011) or if they included similar technology media.
Slides 25-29
Reverences
Connell, C., Bayliss, L. & Farmer, W. (2012). Effects of E-book readers and tablet computers on reading comprehension. International Journal of Instructional Media, 39, (2), 131-140.
Cuevas, J., Russell, R. & Irving, M. (2012). An examination of the effect of customized reading modules on diverse secondary students’ reading comprehension and motivation. Educational Technology Research and Development, 60, 445-467.
Ertem, I. (2010). The effect of electronic storybooks on struggling fourth graders’ reading comprehension. The Turkish Online Journal of Educational Technology, 9, (4), 140-155.
Fry, S. & Gosky, R. (2007/2008). Supporting social studies reading comprehension with an electronic pop-up dictionary. Journal of Research on Technology in Education, 40, (2), 127-139.
Grimshaw, S., Dungworth, N., McKnight, C. & Morris, A. (2007). Electronic books: children’s reading comprehension. British Journal of Educational Technology, 38, (4), 583-599.
Lysenko, L. & Abrami, P. (2014). Promoting reading comprehension with the use of technology. Computers and Education, 75, 162-172.
McNamara, D., O’Reilly, T., Best, R., & Ozuru, Y. (2006). Improving adolescent students’ reading comprehension with iSTART. Journal of Educational Computing Research, 34 (2), 147-171.
Murphy, P. (2007). Reading comprehension exercises online: The effects of feedback, proficiency and interaction. Language Learning & Technology, 11, (3), 107-129.
Ponce, H., Lopez, M. & Mayer, R. (2012). Instructional effectiveness of a computer-supported program for teaching reading comprehension strategies. Computers and Education, 59, 1170-1183.
Ponce, H., Mayer, R. & Lopez, M. (2013). A computer based spatial learning strategy approach that improves reading comprehension and writing. Educational Technology Research Development, 61, 819-840.
Roberts M. & Barber, C. (2013). Effects of reading formats on the comprehension of new independent readers. Journal of Literacy and Technology, 14, (2), 24-55.
Rodriguez, C., Filler, J. & Higgins, K. (2012). Using primary language support via computer to improve reading comprehension skills of first grade English language learners. Computers in the Schools, 29, 253-267.
Salmeron, L. & Garcia, V. (2012). Children’s reading of printed text and hypertext with navigation overviews: The role of comprehension, sustained attention, and visuo-spatial abilities. Journal of Educational Computing Research, 47, (1), 35-50.
Schugar, J, Schugar, H & Penny, C. (2011). A nook or a book: Comparing college students’ reading comprehension level, critical reading, and study skills. International Journal of Technology in Teaching and Learning, 7, (2), 174-192.
Tozcu, A. & Coady, J. (2014). Successful learning of frequent vocabulary through CALL also benefits reading comprehension and speed. Computer Assisted Language Learning, 17, (5), 473-495.
Slide 1
The following is a slidecast of an analytical review of the literature on reading comprehension in technology-based learning.
Slide 2
Reading comprehension has been identified as one of the key factors that affects learners’ overall ability and success in school (Ertem, 2010).
In recent years there has been a growing concern that students are not meeting expectations in this area (McNamara et al., 2006).
Technology-based learning environments offer promising interventions to improve reading comprehension skills (Rodriguez et al., 2012).
They also provide opportunities to increase areas of motivation, interest and engagement, which directly impact reading comprehension (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Murphy, 2007; Roberts & Barber, 2013; Rodriguez et al., 2012).
Slide 3
Methods (no voice over)
Slide 4
This analysis included 15 studies from the years 2004 to 2014 (Roberts & Barber, 2004; Ponce et al., 2013).
The analysis only considered sources with the words reading comprehension as part of their title.
The studies were selected from 12 educational technology journals.
They all included an electronic medium. These media included electronic texts on mobile devices or computers, or educational computer software.
The number of participants in the studies ranged from 28 to 2468.
The analysis excluded meta-analyses and book reviews.
Slide 5
Data collection involved seven studies that were designed to compare text formats. Electronic texts included text on computer, Kindle 3, iPad, CD ROM or Nook (Roberts & Barber, 2013; Ertem, 2010; Fry & Gosky, 2007/2008, Grimshaw et al., 2012; Schugar et al., 2011).
The remaining eight studies tested software programs that were designed by the researchers, purchased, or free online (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al, 2012; Ponce et al., 2013; Rodriguez et al., 2012; Tozcu & Coady, 2004). These programs were designed to improve literacy or reading comprehension.
The participants in the studies were all students in grade one to university.
They were from mainstream and non-mainstream backgrounds.
Participants were studying ESL, language, language arts, science or social studies.
Slide 6
Findings (no voice over)
Slide 7
The literature analysis revealed four categories related to reading comprehension. These were text format, software design, motivation, interest and engagement, and training, support, and resources.
Slide 8
Text Format (no voice over)
Slide 9
The analysis of the literature revealed that reading instruction in technology-based learning resulted in the same reading comprehension gains, regardless of text format (Connell et al,. 2012; Schugar et al., 2011). Only proficient readers performed better with a print text (Roberts & Barber, 2013).
However, it also resulted in significant improvements in reading comprehension using electronic text with animation (Ertem, 2010), narration (Grimshaw et al., 2007) and/or a pop-up dictionary (Fry & Gosky, 2007/2008; Grimshaw et al., 2007).
Reading instruction in technology-based learning environments also resulted in significant improvements for advanced readers who used text with no additional functions (Roberts & Barber, 2013).
Significant improvements for students with low sustained-attention ability were found when students used electronic text with hypertext that had navigation overviews (Salmeron & Garcia, 2012).
Slide 10
Software Design (no voice over)
Slide 11
The analysis revealed that software design that contributed to increased reading comprehension contained specific instruction to support reading comprehension (Ponce et al., 2013) use of graphic organizers (Ponce et al., 2012), elaborative feedback (Murphy, 2007), literacy skills (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu & Coady, 2004) or self-regulation (Lysenko & Abrami, 2014).
In the studies, software that contributed to increased reading comprehension combined its use with prior knowledge of reading strategies (McNamara et al., 2006), independent silent reading (Cuevas et al., 2012) or partner groups (Murphy, 2007).
In one study the use of two software programs combined resulted in significant gains in reading comprehension (Lysenko & Abrami, 2014).
Slide 12
Motivation, Interest, Engagement (no voice over)
Slide 13
In most of the studies, technology-based learning contributed to increased motivation (Cuevas et al., 2012), interest (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Roberts & Barber, 2013; Rodriguez et al., 2012) and/or engagement (Murphy, 2007). Increasing areas of motivation, interest, and engagement positively impacts reading comprehension.
Only Roberts & Barber (2013) found that some grade two participants, the advanced readers, did not demonstrate consistent reading enjoyment with electronic texts. However, their proficient readers demonstrated consistent reading enjoyment.
Slide 14
Training Support, Resources (no voice over)
Slide 15
The analysis revealed that successful implementation of technology-based learning in the classroom required access to teacher support to increase comfort with using computers and to resolve technical issues (Ponce et al., 2012; Ponce et al., 2013).
Another area of need was teacher and student training in how to use computers and software program features (Connell et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Ponce et al., 2013; Schugar et al., 2011). The authors also suggested that training in electronic media may have positively changed the results of their studies.
Computer resources such as the availability of labs was also an issue that was discussed in several studies (Cuevas et al., 2012; Fry & Gosky).
Slide 16
Discussion (no voice over)
Slide 17
The literature analysis presented evidence to demonstrate that reading comprehension is unaffected by text format (Connell et al., 2012; Schugar et al., 2011).
However, reading comprehension was significantly increased with the use of electronic text with narration (Grimshaw et al., 2007), animation (Ertem, 2010) and/or a pop-up dictionary (Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Schugar et al., 2011).
Reading comprehension was also consistently increased using an electronic text with no additional features for advanced readers (Roberts & Barber, 2013) and with navigation overviews for students with low sustained-attention abilities (Salmeron & Garcia, 2012).
Reading comprehension was consistently increased using computer software designed to teach reading comprehension or literacy skills when combined with regular classroom instruction (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Slide 18
Students and teachers should be comfortable using computers to yield significant gains in reading comprehension in technology-based learning environments (Connell et al., 2012, Grimshaw et al., 2007; McNamara et al., 2006; Ponce et al., 2013; Schugar et al., 2011).
They need consistent experiences with software to net maximum benefits in reading comprehension (Ponce et al., 2013; Rodriguez et al., 2012).
Students and teachers need to be familiar with features of devices for maximum gains in reading comprehension (Connell et al., 2012; Schugar et al., 2011).
Slide 19
Conclusion (no voice over)
Slide 20
The findings of almost all of the studies suggested that reading comprehension is unaffected or increased by electronic text formats (Connell et al., 2012; Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Schugar et al., 2011).
Only Roberts & Barber (2013) found that proficient readers performed better with a print text.
If the electronic text included navigation overviews, narration, dictionary or animation, its use promoted significant reading comprehension gains (Salmeron & Garcia, 2012; Grimshaw et al., 2007, Fry & Gosky, 2007/2008; Ertem, 2010).
Reading comprehension in technology-based learning can be augmented through increased motivation, interest and engagement resulting from technology-based learning environments (Cuevas et al., 2012; Ertem, 2010; Grimshaw et al., 2007; Roberts & Barber, 2013; Rodriguez et al., 2012; Murphy, 2007).
Reading comprehension was increased, with the use of technology-based software designed to promote language development or reading comprehension (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Slide 21
Implications (no voice over)
Slide 22
As studies show that using technology based learning results in significant gains for students, teachers can be assured that in many environments or contexts, technology-based learning will effectively promote reading comprehension gains.
Teachers can use electronic texts with narration, animation, hypertext with navigation overviews and/or a pop-up dictionary to increase students’ reading comprehension (Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007).
They can consistently use computer software combined with regular classroom instruction as a means to increase reading comprehension of all students in their classroom (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004).
Researchers can conduct longer study intervention periods which may further impact reading comprehension (Cuevas et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu & Coady, 2004).
They can also investigate the effects that technology-based learning environments have on motivation, interest and engagement, which in turn will positively impact reading comprehension (Cuevas et al., 2012; Ertem, 2010, Grimshaw et al., 2007; Murphy, 2007; Roberts & Barber, 2013; Rodriguez et al., 2012).
Slide 23
Limitations (no voice over)
Slide 24
This analysis included studies with two distinct purposes – to compare text formats (Connell et al., 2012; Ertem, 2010; Fry & Gosky, 2007/2008; Grimshaw et al., 2007; Roberts & Barber, 2013; Salmeron & Garcia, 2012; Schugar et al., 2011) and to study software programs designed to increase reading comprehension and/or literacy skills (Cuevas et al., 2012; Lysenko & Abrami, 2014; McNamara et al., 2006; Murphy, 2007; Ponce et al., 2013; Ponce et al., 2012; Rodriguez et al., 2012; Tozcu & Coady, 2004). The analysis would have been more comprehensive if it focused on one of these major areas.
The results may have differed if the studies controlled for age, general ability or computer ability of the participants.
Many of the studies were conducted over a short period of time. Results may have differed if the studies were longitudinal (Cuevas et al., 2012; Grimshaw et al., 2007; McNamara et al., 2006; Rodriguez et al., 2012; Tozcu &Coady, 2004).
The studies may have also differed if they included larger sample sizes (Rodriguez et al., 2012; Schugar et al., 2011) or if they included similar technology media.
Slides 25-29
Reverences
Connell, C., Bayliss, L. & Farmer, W. (2012). Effects of E-book readers and tablet computers on reading comprehension. International Journal of Instructional Media, 39, (2), 131-140.
Cuevas, J., Russell, R. & Irving, M. (2012). An examination of the effect of customized reading modules on diverse secondary students’ reading comprehension and motivation. Educational Technology Research and Development, 60, 445-467.
Ertem, I. (2010). The effect of electronic storybooks on struggling fourth graders’ reading comprehension. The Turkish Online Journal of Educational Technology, 9, (4), 140-155.
Fry, S. & Gosky, R. (2007/2008). Supporting social studies reading comprehension with an electronic pop-up dictionary. Journal of Research on Technology in Education, 40, (2), 127-139.
Grimshaw, S., Dungworth, N., McKnight, C. & Morris, A. (2007). Electronic books: children’s reading comprehension. British Journal of Educational Technology, 38, (4), 583-599.
Lysenko, L. & Abrami, P. (2014). Promoting reading comprehension with the use of technology. Computers and Education, 75, 162-172.
McNamara, D., O’Reilly, T., Best, R., & Ozuru, Y. (2006). Improving adolescent students’ reading comprehension with iSTART. Journal of Educational Computing Research, 34 (2), 147-171.
Murphy, P. (2007). Reading comprehension exercises online: The effects of feedback, proficiency and interaction. Language Learning & Technology, 11, (3), 107-129.
Ponce, H., Lopez, M. & Mayer, R. (2012). Instructional effectiveness of a computer-supported program for teaching reading comprehension strategies. Computers and Education, 59, 1170-1183.
Ponce, H., Mayer, R. & Lopez, M. (2013). A computer based spatial learning strategy approach that improves reading comprehension and writing. Educational Technology Research Development, 61, 819-840.
Roberts M. & Barber, C. (2013). Effects of reading formats on the comprehension of new independent readers. Journal of Literacy and Technology, 14, (2), 24-55.
Rodriguez, C., Filler, J. & Higgins, K. (2012). Using primary language support via computer to improve reading comprehension skills of first grade English language learners. Computers in the Schools, 29, 253-267.
Salmeron, L. & Garcia, V. (2012). Children’s reading of printed text and hypertext with navigation overviews: The role of comprehension, sustained attention, and visuo-spatial abilities. Journal of Educational Computing Research, 47, (1), 35-50.
Schugar, J, Schugar, H & Penny, C. (2011). A nook or a book: Comparing college students’ reading comprehension level, critical reading, and study skills. International Journal of Technology in Teaching and Learning, 7, (2), 174-192.
Tozcu, A. & Coady, J. (2014). Successful learning of frequent vocabulary through CALL also benefits reading comprehension and speed. Computer Assisted Language Learning, 17, (5), 473-495.