Educational outcomes for youth in foster care are concerning. The achievement gap is close to 1 school year between youth in foster care and the general population (Smithgall, Gladden, Howard, Goerge, & Courtney, 2004). Although there has been research on the educational disparities between youth in foster care and the general population, the field has not yet heard the voices of youth within the system about their educational experiences while in custody.The purposes of this manuscript are to (a) describe a study which engaged youth in foster care in sharing experiences and opinions about their educational successes in a participatory manner, (b) explore the relationship between perceived student engagement and educational outcomes, and (c) harness the suggestions of these youth in policy and practice improvements supporting their educational well-being. IMPLICATIONS FOR PRACTICE •Youth in care are invaluable experts on their experience, and empowering them to share their stories through research creates meaningful policy changes.

The Android platform commands a dramatic majority of the mobile market, and this popularity makes it an appealing target for malicious actors. Android malware is especially dangerous because of the versatility in distribution and acquisition of software on the platform. In this paper, we continue to investigate evolutionary Android malware detection systems, implementing new features in an artificial arms race, and comparing different systems' performances on three new datasets. Our evaluations show that the artificial arms race based system achieves the overall best performance on these very challenging datasets. CCS CONCEPTS • Computing methodologies → Genetic algorithms; • Security and privacy → Malware and its mitigation;

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As more written language data become available, the interest in written language mixing / codeswitching (LM/CS) is increasing (Sebba, Mahootian & Jonsson 2012; Sebba 2013). LM/CS in non-naturalistic (e.g., literary) texts raises issues related to gauging (1) the authenticity and representativity of a textual corpus, and deciding (2) whether categories/mechanisms of spoken LM/CS apply to written LM/CS.1 We focus on Guarani-Spanish LM/CS (Jopara) as represented in the Paraguayan novel Ramona Quebranto (RQ). We apply the framework of Muysken (1997; 2000; 2013), developed as a taxonomy of spoken LM/CS. Our contribution extends its applicability to written LM/CS. We show that Jopara has a mix of insertional and backflagging strategies, with infrequent alternations.