School Dropout as Predicted by Peer Rejection and Antisocial Behavior
By D. French, Jody Conrad. 2001
198 citations recorded by the source corpus.
Subfields: Education
View Paper: https://www.semanticscholar.org/paper/58bdf7550c3be79484112c277fc2a8b8b8e50006
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In Education
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Citations in the corpus
- Social support matters: longitudinal effects of social support on three dimensions of school engagement from middle to high school. (2012, background): “In contrast, peer rejection increases the risk for misconduct, and lower participation and interest in school (French & Conrad, 2001).”
- The Reciprocal Links between School Engagement, Youth Problem Behaviors, and School Dropout during Adolescence (2013, background): “School delinquency may lower emotional engagement by increasing peer rejection and negative attitudes towards school and by lowering youths’ attachment to the institution (Ford, 2005; French & Conrad, 2001).”
- Dropping out of high school: The role of parent and teacher self-determination support, reciprocal friendships and academic motivation (2016, background): “In response to Canadian legislation that permits dropping out of school at the age of 16, some studies have focused on predicting such behavior starting when students are in grade nine (Alivernini & Lucidi, 2011; French & Conrad, 2001; Vallerand, Fortier, & Guay, 1997).”
- Reforming Middle Schools: Focus on Continuity, Social Connectedness, and Engagement (2007, background): “Peers of aggressive–rejected youth indeed often display a wide spectrum of antisocial behaviors (French & Conrad, 2001) unlikely to foster positive relationships with teachers or well-adjusted peers.”
- Victimizing the Children of Immigrants (2009, background): “Low self-perceptions of academic ability (House, 2001), rejection by peers (French & Conrad, 2001), lack of preparation before entering U.S. schools (Rong & Preissle, 1998), and low expectations and future goals (Portes & Rumbaut, 2001) are all reflective of the detrimental school and educational…”
- School Engagement: Potential of the Concept, State of the Evidence (2004, background): “, & Gibson, E. (1996). Peer networks and students' classroom engagement during childhood and adolescence. In J. Juvonen & K. Wentzel (Eds.), Social motivation: Understanding children's school adjustment (pp. 279-312). Cambridge, UK: Cambridge University Press. Krapp, A., Hidi, S., & Renninger, K. A.”
- Prior problem behavior accounts for the racial gap in school suspensions (2014, background): “…patterns can become highly stable ways of interacting – ways of interacting that elevate the likelihood of school discipline, school failure, and dropping out of school later in life (French & Conrad, 2001; Hamre & Pianta, 2001; Loeber, 1982; Loeber & Dishion, 1983; Parker & Asher, 1987).”
- Self-regulated learning: a literature review. [Wider Benefits of Learning Research Report No. 33] (2009, background): “Peer rejection in both childhood and adolescence also increases the probability of dropping out of school (French and Conrad, 2001).”
- Do We Know Who Will Drop Out?: A Review of the Predictors of Dropping out of High School: Precision, Sensitivity, and Specificity (2013, background): “…next page Table 2: Continued Grade Sample Dropout Precision Positive Predictive Sensitivity TruePositive Specificity TrueNegative FalsePositive Proportion 54 ID French and Conrad (2001) Study 8 Level Grade 8 peer rejection and antisocial categories Dropout…”
- Individual characteristics, early adolescent peer affiliations, and school dropout: an examination of aggressive and popular group types (2003, background): “French and Conrad (2001) found that school dropoutwas associatedwith early adolescent aggression but not social preference.”
- Attachment in the Classroom (2009, background): “…disabilities, more attention and thought problems, and greater risk of dropping out (Bub et al. 2007; Buhs and Ladd 2001; Dishion et al. 1991; French and Conrad 2001; Horn and Packard 1985; Hymel et al. 2002; Ladd and Burgess 2001; Malecki and Elliot 2002; Trzesniewski et al. 2006; Wentzel…”
- A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes (2015, background): “A myriad of reasons ranging from economic problems, lack of motivation, and unexpected life changes can delay students’ graduation or cause them to drop out [7, 13, 24].”