Direct-Instruction Tutoring for Academic Performance

Using Direct-Instruction Tutoring to Improve Academic Performance in Out-Of-Home Care Children

Social Policy Proposal

Differences in academic achievement is a concept greatly studied in social psychology. There exists a cornucopia of studies investigating issues surrounding the concept with relation to gender, generational, ethnic and class differences (Gil & Carvalho, 2016, Duong, Badaly, Liu, Schwartz, Mccarty, Carolyn, 2016, Stephens, Witkow & Fuligni, 2011, Hamedani & Destin, 2014). However, one far less studied area is the reduced educational attainment found in children placed in ‘out-of-home care’ (OHC). Out-of-home care refers to children under 18 years who are unable to live with their families, often due to neglect or abuse. It involves the placement of a child in an institutional setting, or with alternate caregivers. The following proposal shall outline examples of such decreased academic performance, as well as discuss the theory of school engagement as a possible explanation. Furthermore, a solution to the issue shall be proposed with respect to a direct-instruction programme.

Get Help With Your Essay

If you need assistance with writing your essay, our professional essay writing service is here to help!
Find out more about our Essay Writing Service

The issue at hand is vast, with OHC children displaying a tendency to largely experience poor life outcomes when compared to children in the general population. Such disparities are visible across many psychosocial dimensions. Higher risk of teenage pregnancy and STD contraction (Dworsky & Courtney, 2010), increased levels of homelessness (Brown & Wilderson, 2010) and higher rates of substance abuse and mental health issues (Villegas & Pecora, 2012) are all documented problems. However, this is most obvious in regards to academic achievement. OHC children often lag one or two years behind their peers in the general population (Trout, Hagaman, Casey, Reid, & Epstein, 2008) and are less likely to obtain a diploma, graduate past secondary or enrol in higher education (Villegas & Pecora, 2012). At Key Stage 2, 48% of children in care reached the expected academic level in English and mathematics, compared to 79% of all children. The attainment gap continues to increase as children get older: 7% of OHC children go on to attend university, compared to just over 50% of young people in the general population (O’Higgins, Sebba, Luke, 2015). Such underperformance in OHC children has been found to be predictive of negative effects in the future, such as criminal convictions and self-harm (Forsman, Brännströma, Vinnerljunga, Hjernb, 2016).

One explanation for this disparity between OHM children and the general population can be seen in the theory of school engagement (Wang, Willett & Eccles, 2011). This theory suggests that academic performance can be categorized into two dimensions of school engagement. ‘Cognitive engagement’ refers to the level to which the student participates in classroom learning and their ability to regulate such effort. Cognitive engagement is often correlated with grade attainment or test performance (Li & Lerner, 2013). The second, ‘affective engagement’. This refers to how students perceive their school experience, incorporating their connection to their school, investment in class and relationship with their teachers. There are various studies which highlight the link between school engagement and educational performance. For example, Wang and Holcombe (2010) found school engagement to be directly related to academic achievement as well as functioning and adjustment in the school environment. Low levels of school engagement have also been attributed to delinquency, substance abuse (Li & Lerner, 2011) higher drop-out rates (Archambault, Janosz, Fallu & Pagani, 2009) and anti-social behaviour (Andrews & Duncan, 1997). Decline can also be attributed to bullying, cheating, aggression and conduct issues (Simons-Morton and Chen, 2009).

Reasons for the reduction in affective and cognitive engagement seen in OHC children can be seen in studies of other risk-populations which suggest such children are likely to experience less resources, decreased social support, higher-risk environments and increased exposure to adversity (Marks, 2000 and Daly, Shin, Thakral, Selders, & Vera, 2009). Furthermore, a study by Gruman, Harachi, Abbott, Catalano & Fleming (2008) found that children in OHC experience constant mobility and changes in placement which disrupts their school attendance, negatively affecting their school engagement. This can be seen in a study by Pears, Kim, Fisher and Yoerger’s (2013) which found that as well as displaying higher levels of externalizing and risk behaviours, children from a foster care sample showed significantly lower mean levels of affective and cognitive engagement in comparison to the children in a control group. This therefore suggests that due to their unstable environment, children in OHC exhibit less cognitive and affective engagement in school, thus hindering their academic performance.

Therefore, one way in which to challenge the disparity between OHC and normal children may be to address their lack of school engagement. A method in which to help decreased cognitive and affective engagement can be seen in ‘direct-instruction’ (DI) interventions. DI is a specific style of teaching which has been used in many educational programmes designed for at-risk students. It consists of explicit, systematic instructions based on pre-planned lessons, a minimal student-to-teacher ratio, and constant assessment and progress tracking (Stahl, Duffy-Hester & Stahl, 1998). DI programmes usually employ a three-step instructional procedure. Teachers must model (provide the appropriate information), lead (implore the correct recall from the student), and test (give immediate feedback and a delayed probe on the task initially attempted (Margaret, Houchins, Steventon, Candace & Donya, 2005). DI programmes contain certain elements which can directly enhance aspects of cognitive and affective engagement for which OHC children are lacking in with regards to their normal school environment. This can be implemented via the application of supplementary tutoring programmes such as the TYCW (Maloney, 1998 in Flynn et al, 2012), DISTAR (Kim & Axelrod, 2005) and the DILC (Cadette, Wilson, Brady, Dukes & Bennett, 2016) which follow a DI approach. Such tutoring interventions could be administered by foster parents or carers as part of an institutional or foster care programme for OHC children.

The explicit approach of DI has been found to help improve cognitive engagement, made evident through a wealth of literature attaining to how DI programmes can help improve overall grades in disadvantaged children. In a meta-analysis conducted by Borman, Hewes, Overman and Brown (2003), DI was found to be one of the most efficient programmes for improving academic performance in underachieving urban schools. The DI approach was also found to be effective in improving academic outcomes for young people at risk of school failure (Dolezal, Weber, Evavold, Wylie, & McLaughlin, 2007). This implies DI programmes are useful to tackling cognitive engagement as it aims at improving academic performance in class. In terms of OHC children, a study by (Flynn, Marquis, Paquet, Peeke & Aubry, 2012) conducted a randomized effectiveness trial with 77 foster children who were either involved in an DI intervention programmed or placed in a control group. Results indicated that at the post-test, the foster children in the experimental group had made statistically and practically greater gains for sentence comprehension, reading and maths computation than those in the control group with relation to the pre-test scores.

There is evidence for the ability DI programmes to address affective engagement also. DI improves student investment in class by minimizing the student-teacher ratio, ensuring that students receives more attention, thus increasing their connection with their teacher and bettering their overall experience (Rodriguez & Elbaum, 2014). As the number of students increase, there is a reduction in the amount of time that can be spent on instruction and dealing with individual children (Bennett, 1996). This balance helps progress interactions between student and teacher and improves the relationship between the two. This improvement in the classroom experience is best illustrated in studies exploring the effects of classroom size in the achievement of at-risk pupils. For instance, a study by Blatchford, Bassett and Brown (2011) found that smaller classes led to pupils receiving more individual attention from teachers, and having better interactions with them. It was also reported that school engagement decreased in larger classes and that disadvantaged and minority pupils can benefit from a reduction in the student-teacher ratio in terms of more individual attention and facilitating engagement in learning (Finn, Suriani, & Achilles, 2007 in Rodriguez & Elbaum, 2014).

In conclusion, it is clear, that children in OHC suffer from poorer academic achievement then those in the general population. The unstable environment experienced by such children during their academic years effects their ability to engage in classroom activities and general learning. The solution proposed to address this issue encompasses the introduction of tutoring programmes for such children in-line with the structure of DI interventions. Used in compliment to their school education such programmes work to enhance the decreased cognitive and affective engagement these pupils demonstrate in their regular school environment. Introducing such interventions in OHC institutions and foster care programmes should help to minimize the academic disparity between such children and their peers.

References

1. Carvalho, R. & Gil, G. (2016). Gender differences in academic achievement: The mediating role of personality, Personality and Individual Differences, 94, 54-58
2. Duong, M.T., Badaly, D., Liu, F.L., Schwartz, D., Mccarty, C.A. (2016). Generational Differences in Academic Achievement among Immigrant Youths: A Meta-Analytic Review, Review of Educational Research, 2016, 86(1), 15-23
3. Witkow, M.R. & Fuligni, A.J. (2011) Ethnic and Generational Differences in the Relations between Social Support and Academic Achievement across the High School Years, Journal of Social Issues, 67(3), 531-552
4. Stephens, N.M., Hamedani, M.G & Destin, M. (2014) Closing the social-class achievement gap: a difference-education intervention improves first-generation students’ academic performance and all students’ college transition, Psychological science, 25(4), 943-53
5. Dworsky, A. & Courtney, M.E. (2010) The risk of teenage pregnancy among transitioning foster youth: Implications for extending state care beyond age 18, Children and Youth Services Review, 32(10), 1351-1356
6. Brown, S. & Wilderson, D. (2010) Homelessness prevention for former foster youth: Utilization of transitional housing programs, Children and Youth Services Review, 32(10), 1464-1472
7. Villegas, S. & Pecora, P.J. (2012). Mental health outcomes for adults in family foster care as children: An analysis by ethnicity, Children and Youth Services Review, 34(8), 1448-1458
8. Trout, A. L., Hagaman, J., Casey, K., Reid, R., & Epstein, M. H. (2008). The academic status of children and youth in out-of-home care: A review of the literature. Children and Youth Services Review, 30, 979-994
9. O’Higgins, A., Sebba, J. & Luke, N. (2015). What is the relationship between being in care and the educational outcomes of children? An international systematic review, The Rees Centre for Research in Fostering and Education, University of Oxford.
10. Forsman, H., Brännström, L., Vinnerljung, B. & Hjern, A. (2016). Does poor school performance cause later psychosocial problems among children in foster care? Evidence from national longitudinal registry data, Child Abuse & Neglect, 57, 61-71
11. Wang, M.T., Willett, J.B., Eccles, J.S. (2011). The Assessment of School Engagement: Examining Dimensionality and Measurement Invariance by Gender and Race/Ethnicity, Journal of School Psychology, 49(4), 465-480
12. Li, Y. and Lerner, M. (2013). Interrelations of behavioural, emotional, and cognitive school engagement in high school students, Journal Youth Adolescence, 42, 20-32
13. Wang, M.T., Holcombe, R. (2010) Adolescents’ Perceptions of School Environment, Engagement, and Academic Achievement in Middle School, American Educational Research Journal, 47(3), 633-662
14. Li, Y. Lerner, R.M. 2011) Trajectories of School Engagement during Adolescence: Implications for Grades, Depression, Delinquency, and Substance Use, Developmental Psychology, 47(1), 233-247
15. Chen, R. & Simons-Morton, B. (2009) Concurrent changes in conduct problems and depressive symptoms in early adolescents: A developmental person-centred approach, Development and Psychopathology, 21(1), 285-307
16. Andrews, J. & Duncan, S. (1997). Examining the Reciprocal Relation Between Academic Motivation and Substance Use: Effects of Family Relationships, Self-Esteem, and General Deviance, Journal of Behavioural Medicine, 20(6), 523-549
17. Archambault, I., Janosz, M., Fallu, J.S., Pagani, L.S. (2009). Student Engagement and Its Relationship with Early High School Dropout, Journal of Adolescence, 32(3), 651-670
18. Pears, K.C., Kim, H.K., Fisher, P.A. and Yoerger, K. (2013). Early school engagement and late elementary outcomes for maltreated children in foster care.  Developmental Psychology, 49(12), 2201-2211
19. Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle, and high school years. American Educational Research Journal, 37, 153-184
20. Daly, B. P., Shin, R. Q., Thakral, C., Selders, M., & Vera, E. (2009). School engagement among urban adolescents of colour: Does perception of social support and neighbourhood safety matter? Journal of Youth and Adolescence, 38, 63-74
21. Gruman, D. H., Harachi, T. W., Abbott, R. D., Catalano, R. F., & Fleming, C. B. (2008). Longitudinal effects of student mobility on three dimensions of elementary school engagement. Child Development, 79, 1833-1852.
22. Stahl, S., Duffy-Hester, A., & Stahl, K. (1998). Everything you wanted to know about
23. phonics (but were afraid to ask). Reading Research Quarterly, 33, 338-355
24. Margaret E., Houchins, D.E., Steventon, C. & Sartor, D. (2005) A Comparison of Two Direct Instruction Reading Programs for Urban Middle School Students, Remedial and Special Education, 26(3), 175-182
25. Kim, T. & Axelrod, S. (2005). Direct Instruction: An Educators’ Guide and a Plea for Action, The Behaviour Analyst Today, 6(2), Page 111-123
26. Cadette, J.N., Wilson, C.L., Brady, M.P., Dukes, C., Bennett, K.D. (2016) The Effectiveness of Direct Instruction in Teaching Students with Autism Spectrum Disorder to Answer “Wh-” Questions, Journal of Autism and Developmental Disorders, 46(9), 2968-2978
27. Borman GD, Hewes GM, Overman LT, Brown S. (2003). Comprehensive school reform and achievement: A meta-analysis, Review of Educational Research, 73(2), 125-230.
28. Dolezal, D.N., Weber, K.P., Evavold, J.J., Wylie, J., Mclaughlin, T. F (2007).The Effects of a Reinforcement Package for On-Task and Reading behaviour with At-Risk and Middle School Students with Disabilities, Child & Family behaviour Therapy, 29(2), 9-25
29. Flynn, R.J., Marquis, R.A., Paquet, M.P., Peeke, L.M. & Aubry, T.D. (2012). Effects of individual direct-instruction tutoring on foster children’s academic skills: A randomized trial, Children and Youth Services Review, 34(6), 1183-1189
30. Rodriguez, R. J. & Elbaum, B. (2014) The Role of Student-Teacher Ratio in Parents’ Perceptions of Schools’ Engagement Efforts, Journal of Educational Research, 107(1), 69-80
31. Blatchford, P., Bassett, P. & Brown, P. (2011) Examining the Effect of Class Size on Classroom Engagement and Teacher-Pupil Interaction: Differences in Relation to Pupil Prior Attainment and Primary vs. Secondary Schools, Learning and Instruction, 21(6), 715-730
32. Bennett, N. (1996). Class size in primary schools: Perceptions of head teachers, chairs of governors, teachers and parents, British Educational Research Journal, 22(1), 33 – 55