The aim of this study is to explore how peer support workers (individuals with similar lived experiences employed to provide support) conceptualize change work with young people experiencing homelessness. The present study used participatory qualitative methods, including semistructured interviews and journaling with peer support workers and program supervisors and administrators, to understand how peers understand change work with young people experiencing homelessness. This study found that peers center self-directed growth among young people experiencing homelessness, rather than change that prioritizes meeting program-directed outcomes such as obtaining housing or gaining employment. Peer relationships invite possibility and create containers of hope when supporting young people experiencing homelessness, regardless of their paths. Lastly, peers recognize that growth happens in seasons, and embrace such seasons as checkpoints on youths' journeys. Such findings may guide service providers beginning peer programming or those considering models for engaging young people experiencing homelessness in relationship-supported growth.

The use of a Classroom Response System (CRS) was evaluated in two sections, A and B, of a large lecture microbiology course. In Section B the instructor used the CRS technology at the beginning of the class period posing a question on content from the previous class. Students could earn extra credit if they answered the question correctly. In Section A, the class also began with an extra credit CRS question. However, CRS questions were integrated into the lecture during the entire class period. We compared the two classes to see if augmenting lectures with this technology increased student learning, confidence, attendance, and the instructor's ability to respond to student's misconceptions, over simply using the CRS as a quizzing tool. Student performance was compared using shared examination questions. The questions were categorized by how the content had been presented in class. All questions came from instructors' common lecture content, some without CRS use, and some questions where Instructor A used both lecture and CRS questions. Although Section A students scored significantly better on both types of examination questions, there was no demonstrable difference in learning based on CRS question participation. However, student survey data showed that students in Section A expressed higher confidence levels in their learning and knowledge and indicated that they interacted more with other students than did the students in Section B. In addition, Instructor A recorded more modifications to lecture content and recorded more student interaction in the course than did Instructor B.Because of increasing enrollments and tighter budgets, colleges are offering larger classes as a way to save money (5, 12). Consequently, faculty-student ratios in many introductory courses range from 1:100 to 1:500. While studies show mixed results in determining what effect class size has on student performance, a trend does emerge-new students or students with lower achievement levels have trouble in larger classes (3, 9).The current theory of learning, constructivism, is one where learning is an interpretive, recursive, building process whereby learners actively participate in the learning process in order to make meaning of new information and constructs so as to internalize this understanding as part of their own knowledge base (10). Therefore, attention to the limits of large class sizes is essential in order to maximize student achievement. Large classes inhibit types of instructional methods, strategies, and activities that are consistent with constructivism in four ways. First, learners need to make meaning of the new information in order to assimilate it into their existing knowledge base (19). Without meaning, information is often forgotten after a short period of time. As a result, learners need to interact with this new information in some way. Large classes limit this interaction, and the brief time allotted for instruction constrains the types of instructional strategies and activities that can be used to allow students ...

Colleges and universities interact with multiple constituents or quality monitoring groups that require programme-level assessment of student learning. These required assessments might be used to demonstrate accountability, programme improvement or a combination of both. These demands often challenge instructional faculty to choose between the competing interests of research in their discipline and research on student learning for assessment purposes. This article offers one approach for engineering departments that simultaneously makes student learning research more meaningful for instructional faculty while farming out to the central administration those jobs it does not have the time or resources to do effectively. An engineering programme is better able to ensure the ownership, development and integrity of and research into its own curriculum if it has a centralized university improvement system that presents unit-level quality management research to external market and accountability groups.

Flexible Airspace Management (FAM) is a midterm Next Generation Air Transportation System (NextGen) concept that allows dynamic changes to airspace configurations to meet the changes in the traffic demand. A series of human-in-the-loop (HITL) studies have identified procedures and decision support requirements needed to implement FAM. This paper outlines a suggested FAM procedure and associated decision support functionality based on these HITL studies. A description of both the tools used to support the HITLs and the planned NextGen technologies available in the mid-term are presented and compared. The mid-term implementation of several NextGen capabilities, specifically, upgrades to the Traffic Management Unit (TMU), the initial release of an en route automation system, the deployment of a digital data communication system, a more flexible voice communications network, and the introduction of a tool envisioned to manage and coordinate networked ground systems can support the implementation of the FAM concept. Because of the variability in the overall deployment schedule of the mid-term NextGen capabilities, the dependency of the individual NextGen capabilities are examined to determine their impact on a mid-term implementation of FAM. A cursory review of the different technologies suggests that new functionality slated for the new en route automation system is a critical enabling technology for FAM, as well as the functionality to manage and coordinate networked ground systems. Upgrades to the TMU are less critical but important nonetheless for FAM to be fully realized. Flexible voice communications network and digital data communication system could allow more flexible FAM operations but they are not as essential.

Flexible Airspace Management (FAM) is a midterm Next Generation Air Transportation System (NextGen) concept that allows dynamic changes to airspace configurations to meet the changes in the traffic demand. A series of human-in-the-loop (HITL) studies have identified procedures and decision support requirements needed to implement FAM. This paper outlines a suggested FAM procedure and associated decision support functionality based on these HITL studies. A description of both the tools used to support the HITLs and the planned NextGen technologies available in the mid-term are presented and compared. The mid-term implementation of several NextGen capabilities, specifically, upgrades to the Traffic Management Unit (TMU), the initial release of an en route automation system, the deployment of a digital data communication system, a more flexible voice communications network, and the introduction of a tool envisioned to manage and coordinate networked ground systems can support the implementation of the FAM concept. Because of the variability in the overall deployment schedule of the mid-term NextGen capabilities, the dependency of the individual NextGen capabilities are examined to determine their impact on a mid-term implementation of FAM. A cursory review of the different technologies suggests that new functionality slated for the new en route automation system is a critical enabling technology for FAM, as well as the functionality to manage and coordinate networked ground systems. Upgrades to the TMU are less critical but important nonetheless for FAM to be fully realized. Flexible voice communications network and digital data communication system could allow more flexible FAM operations but they are not as essential.