Free Paper Example on Digitization as a Pedagogical Practice

Use of technology in the early childhood education

Currently, technology has played a significant role in improving education at different levels. According to Jennifer et al., 2016, screen media have become common in the life of young children. This issue makes it essential to understand the influence of specific technologies including e-books or tablets for literacy and the best ways of including them in the kid's routine both at home and in the classroom. Jennifer et al., 2016 tried to find out what Science of Learning tells people concerning the features of applications which can increase or decrease educational potential. The findings generated with Science of Learning in identifying the characteristics of apps with the right educational potential include the fact that learning takes place when the learner is active, engaged, when the content is meaningful, when learning is exploited by social interaction, and when the guided exploration in a learning goal is best (Jennifer et al., 2016; Zosh et al., 2016 ). Jennifer et al., 2016 concluded that even though apps are useful in learning, app developers, parents, educators, and policymakers should use science on the way children learn to assist in the evaluation and creation of applications.

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In the recent years, there has been a quick expansion of tablet computers in both schools and households. The educational affordances of the tablet computers include the utilization of math apps in engaging students in their mathematical learning (Zhang, 2015). However, there is little research on the effectiveness of math applications for the struggling students. In filling in this gap, Zhang (2015) researched fourth graders in which half of the students had disabilities or were at risk. The study conducted also found out that the usage of math apps improved student learning and even close the achievement gap that exists between typical and struggling students.

Use of robots in the education of young children

Robots is one of the technologies that have been used in the education of the young children. The rapid development of technology in this 21st century has made the use of several media tool in education to be popular. Notwithstanding their engineering applications and robots are being used in schools. Toh et al., (2016) synthesized findings of research studies for the past ten years and the impact of robots on education and children. The main factors that were examined include the impact of robots on children's development and behavior, the perception of stakeholders (educator, children, and parents) on educational robots, and the reaction of the children on robot appearance and design. The review also shows the model used with researchers validates the use of robots that includes non-experimental (longitudinal, mixed method, case studies, anecdotal, and cross-sectional) and quasi-experimental (Toh et al., 2016). The findings of Toh indicated that the robot has an influence on the children's skills development that can be grouped into language, cognitive, social, and conceptual skills. The mixed results also indicated that the parent's perceptions on the use of robots on kid's education while designing influenced the perception of robots capabilities and characters ((Toh et al., 2016; Zosh et al., 2016).

Helping students who are struggling to read

The students who have behavioral and do experience emotional disorders do experience deficits in academic, social, and behavioral areas and of primary importance in academic area is the achievement of reading(Louick et al., 2016; Mcdaniel, Duchaine, & Jolivette, 2010). Students that have emotional and behavioral disorders who struggle to read do have negative in both school and post-school outcomes. It is significant to efficiently remediate reading problems of the students with E/BD because of the severity of the results (Mcdaniel, Duchaine, & Jolivette, 2010). This study also examined the perceptions of students and teachers who took part in the eight-week Corrective Reading intervention and they regarded it helpful as it enabled them to know the areas they should improve. Mcdaniel, Duchaine, and Jolivette, (2010) used the interview method in getting more information concerning the issue of E/BD.

Ways of helping students with E/BD

One of the ways of helping the students who are suffering from emotional and behavioral disorders include individualizing instruction (Mcdaniel, Duchaine, and Jolivette, 2010; Stover, Sparrow, & Siefert, 2017). It is the easiest way of helping those students since there will be a productive teacher-student relationship. Although there have been sound instructional practices of developing foundational reading skills with the young learners, several learners have continued to lag behind in learning literacy. Most do not usually view themselves as readers, lack of motivation makes them become disengaged in learning in general (Stover, Sparrow, & Siefert, 2017; Louick et al., 2016). Stover, Sparrow, and Siefert (2017) share a research-based instructional framework that was developed with one of the authors (Sparrow) that taught a struggling reader. The attitudinal survey was also conducted, and it revealed that the learner's interest in dump trucks and tractors. With the information that was acquired, the student's interest and differentiated instruction in meeting his unique needs were regarded. In essence, the tutee also engaged in learning which further developed his self-efficacy as a reader (Stover, Sparrow, & Siefert, 2017). Therefore, the authors think that posit of this instructional method might inform the mainstream teachers that continue seeking the ways of improving literacy success to all the learners.

Motivation

Motivation can be utilized as a tool for reading among the struggling middle-class readers. Louick et al., 2016 explored Reading Comprehension for 112 struggling middle-class readers on urban and semi-urban areas and the data sources used include self-reported reading surveys and random student motivation interviews. Hierarchical linear modelling was also applied in modelling growth in RC and evaluating the three elements of motivational reading-intrinsic, extrinsic, and self-efficacy motivation to slopes and intercepts of reading comprehension (Louick et al., 2016). The interviews with the students were coded for the albescence and presence of the three motivation constructs. Even though interview and HLM analysis were concurrently done, follow up analysis were also conducted using each of the data technique basing on the initial findings. The main findings that emerged from the study include the essential impact of self-efficacy on the initial RC status and paradoxical site differences in that semi-urban students had high RC scores while urban sites had high motivation scores. The other finding is that the quantitative influence of self-efficacy which predicts that RC can be well explained through qualitative findings that the struggling readers hold several motivational beliefs that influence them differently depending on the learning environment.

Improving student's learning effectiveness

The research that was conducted with Wang used both Web-based dynamic assessment and Web-based two-tier diagnostic assessment in developing a centered e-learning system called 'GPAM-WATA e-Learning system.' The system has two main designs including personalized, dynamic assessment and personalized e-learning annotation Wang, T. H. (2014). Additionally, the research adopted quasi-experimental design to apply GPAM-WATA e-Learning system in teaching Speed unit in the mathematical course. 107 6th graders from (4 classes) in the elementary Scheel took part in the research. According to Wang (2014), before the remedial classes, all the students got prior knowledge valuation and pretest both summative and two-tier diagnostic assessment. The students then received remedial teaching, and they completed all the teaching activities. After the remedial, the student took a post-test of two-tier diagnostic and summative assessment. The limitation of the research is that it does not predict the student's improvement of misconceptions and learning achievement. Wang (2014), then concluded that e-learning models having personalized, dynamic assessment is more efficient in facilitating the learning achievement of a student. However, personalized e-learning adaptive annotation influences the percentage of the reading time the students spend on eLearning materials that they use to enhance learning.

References

Louick, R., Leider, C. M., Daley, S. G., Proctor, C. P., & Gardner, G. L. (2016). The motivation for reading among struggling middle school readers: A mixed methods study. Learning and Individual Differences, 49, 260-269. DOI:10.1016/j.lindif.2016.06.027

Mcdaniel, S. C., Duchaine, E. L., & Jolivette, K. (2010). Struggling Readers with Emotional and Behavioral Disorders and Their Teachers: Perceptions of Corrective Reading. Education and Treatment of Children, 33(4), 585-599. DOI:10.1353/etc.2010.0009

Stover, K., Sparrow, A., & Siefert, B. (2017). "It ain't hard no more!" Individualizing instruction for struggling readers. Preventing School Failure: Alternative Education for Children and Youth, 61(1), 14-27. DOI: 10.1080/1045988X.2016.1164659

Toh, E., Poh, L., Causo, A., Tzuo, P. W., Chen, I., & Yeo, S. H. (2016). A Review on the Use of Robots in Education and Young Children. Journal of Educational Technology & Society, 19(2). https://www.jstor.org/stable/jeductechsoci.19.2.148

Wang, T. H. (2014). Developing an assessment-centered e-Learning system for improving student learning effectiveness. Computers & Education, 73, 189-203. DOI:10.1016/j.compedu.2013.12.002

Zhang, M., Trussell, R. P., Gallegos, B., & Asam, R. R. (2015). Using math apps for improving student learning: An exploratory study in an inclusive fourth-grade classroom. TechTrends, 59(2), 32-39. DOI: 10.1007/s11528-015-0837-y

Zosh, J. M., Hirsh-Pasek, K., Golinkoff, R. M., & Parish-Morris, J. (2016). Learning in the Digital Age: Putting Education Back in Educational Apps for Young Children.