Flip your classroom: Reach every student in every class every day

I. INTRODUCTION TO EVALUATION. 1. Evaluation's Basic Purpose, Uses, and Conceptual Distinctions. 2. Origins of Modern Program Evaluation. 3. Recent Developments and Trends in Evaluation. II. ALTERNATIVE APPROACHES TO PROGRAM EVALUATION. 4. Alternative Views of Evaluation. 5. Objectives-Oriented Evaluation Approaches. 6. Management-Oriented Evaluation Approaches. 7. Consumer-Oriented Evaluation Approaches. 8. Expertise-Oriented Evaluation Approaches. 9. Adversary-Oriented Evaluation Approaches. 10. Participant-Oriented Evaluation Approaches. 11. Alternative Evaluation Approaches: A Summary and Comparative Analysis. III. PRACTICAL GUIDELINES FOR PLANNING EVALUATION. 12. Clarifying the Evaluation Request and Responsibilities. 13. Setting Boundaries and Analyzing the Evaluation Context. 14. Identifying and Selecting the Evaluative Questions and Criteria. 15. Planning How to Conduct the Evaluation. IV. PRACTICAL GUIDELINES FOR CONDUCTING AND USING EVALUATIONS. 16. Dealing with Political, Ethical, and Interpersonal Aspects of Evaluation. 17. Collecting, Analyzing, and Interpreting Quantitative Information. 18. Collecting, Analyzing, and Interpreting Qualitative Information. 19. Reporting and Using Evaluation Information. 20. Evaluating Evaluations. V. EMERGING AND FUTURE SETTINGS FOR PROGRAM EVALUATION. 21. Conducting Multiple-Site Evaluation Studies. 22. Conducting Evaluations of Organizations Renewal and Training in Corporate and Nonprofit Settings. 23. The Future of Evaluation. Appendix: Some General Areas of Competence Important in Education Evaluation.

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تقويم البرنامج : طرق بديلة و إرشادات عملية = Program evaluation Alternative Approaches and Practical Guidelines

Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Transportation network analysis

The transport system is critical to the welfare of modern societies. This article provides an overview of recent research on vulnerability and resilience of transport systems. Definitions of vulnerability and resilience are formulated and discussed together with related concepts. In the increasing and extensive literature of transport vulnerability studies, two distinct traditions are identified. One tradition with roots in graph theory studies the vulnerability of transport networks based on their topological properties. The other tradition also represents the demand and supply side of the transport systems to allow for a more complete assessment of the consequences of disruptions or disasters for the users and society. The merits and drawbacks of the approaches are discussed. The concept of resilience offers a broader socio-technical perspective on the transport system’s capacity to maintain or quickly recover its function after a disruption or a disaster. The transport resilience literature is less abundant, especially concerning the post-disaster phases of response and recovery. The research on transport system vulnerability and resilience is now a mature field with a developed methodology and a large amount of research findings with large potential practical usefulness. The authors argue that more cross-disciplinary collaborations between authorities, operators and researchers would be desirable to transform this knowledge into practical strategies to strengthen the resilience of the transport system.

Vulnerability and resilience of transport systems : A discussion of recent research

This paper develops an equilibrium modeling framework that captures the interactions among availability of public charging opportunities, prices of electricity, and destination and route choices of plug-in hybrid electric vehicles (PHEVs) at regional transportation and power transmission networks coupled by PHEVs. The modeling framework is then applied to determine an optimal allocation of a given number of public charging stations among metropolitan areas in the region to maximize social welfare associated with the coupled networks. The allocation model is formulated as a mathematical program with complementarity constraints, and is solved by an active-set algorithm. Numerical examples are presented to demonstrate the models and offer insights on the equilibrium of the coupled transportation and power networks, and optimally allocating resource for public charging infrastructure.

Optimal deployment of public charging stations for plug-in hybrid electric vehicles

This paper investigates congestion pricing strategies in static networks with boundedly rational route choice behavior. Under such behavior, users do not necessarily choose a shortest or cheapest route when doing so does not reduce their travel times by a significant amount. A general path-based definition and a more restrictive link-based representation of boundedly rational user equilibrium (BRUE) are presented. The set of BRUE flow distributions is generally non-convex and non-empty. The problems of finding best- and worst-case BRUE flow distributions are formulated and solved as mathematical programs with complementarity constraints. Because alternative tolled BRUE flow distributions exist, our congestion pricing models seek a toll vector or pattern that minimizes the system travel time of the worst-case tolled BRUE flow distribution. As formulated, the models are generalized semi-infinite min–max problems and we propose a heuristic algorithm based on penalization and a cutting-plane scheme to solve them. Numerical examples are presented to illustrate key concepts and results.

Robust congestion pricing under boundedly rational user equilibrium

Given that the cumulative prospect theory provides a well-supported descriptive paradigm for decision making under risk or uncertainty, previous studies applied the theory to model travelers' route choice behaviors in stochastic networks and prospect-based user equilibrium models. The models rely on exogenous inputs of reference points and thus the resulting reference-dependence could be regarded as an ad hoc assumption. This paper proposes a conjecture on travelers' determination of reference points and encapsulates it into the prospect-based user equilibrium conditions. The conditions are formulated as an equivalent variational inequality and a heuristic solution algorithm is proposed to solve it. Both the model and the solution algorithm are demonstrated in two numerical examples. As one application, this paper further develops an optimal pricing model in which the proposed user equilibrium model is adopted to capture travelers' response to pricing signals under risk. The pricing model is formulated as a mathematical program with complementarity constraints, solved by a derivative-free algorithm. Another numerical example is presented to illustrate the pricing model and the solution algorithm.

A prospect-based user equilibrium model with endogenous reference points and its application in congestion pricing

This paper proposes two sensible approaches that may be potentially implemented in practice to determine pricing strategies for operating managed toll lanes. The tolls vary dynamically in response to real-time traffic conditions in order to provide a superior free-flow travel service to the users of the toll lanes while maximizing the freeway’s throughput. Simulation experiments are conducted to validate and compare the proposed approaches.

Dynamic Tolling Strategies for Managed Lanes

This paper proposes a self-learning approach to determine optimal pricing strategies for high-occupancy/toll lane operations. The approach learns recursively motorists’ willingness to pay by mining the loop detector data, and then specifies toll rates to maximize the freeway’s throughput while ensuring a superior travel service to the users of the toll lanes. In determination of the tolls, a multi-lane hybrid traffic flow model is used to explicitly consider the impacts of the lane-changing behaviors before the entry points of the toll lanes on throughput and travel time. Simulation experiments are conducted to demonstrate and validate the proposed approach, and provide insights on when to convert high-occupancy lanes to toll lanes.

Optimal dynamic pricing strategies for high-occupancy/toll lanes

This paper proposes a self-learning approach for determining pricing strategies for high-occupancy/toll lane operations. The approach learns recursively motorists’ willingness to pay by mining the loop detector data, and specifies toll rates to maximize the freeway’s throughput while ensuring a superior free-flow travel service to the users of the toll lanes. In determination of the tolls, a multi-lane hybrid traffic flow model is used to explicitly consider the impacts of the lane-changing behaviors before the entry points of the toll lanes. Simulation experiments are conducted to demonstrate and validate the proposed approach, and provide insights on when to convert high-occupancy lanes to toll lanes.

Yingyan Lou

Papers

Robust congestion pricing under boundedly rational user equilibrium

A prospect-based user equilibrium model with endogenous reference points and its application in congestion pricing

Dynamic Tolling Strategies for Managed Lanes

Optimal dynamic pricing strategies for high-occupancy/toll lanes

Optimal Dynamic Pricing Strategies for High-Occupancy/Toll Lanes