Optimising information literacy delivery to large classes: the contact or the online approach?

DCU Business School runs undergraduate programmes of varying sizes, from 40 to 200 students. Some modules cross disciplines and attract even higher numbers. One such module is HR118: Skills for success which in the last year has exceeded 200. Even this number is restrained by the optional nature of the module. Were it to be an obligatory module, the total would exceed 300. The Library has been providing embedded information literacy sessions to HR118 since its inception, providing face-to-face training on essential resources and research techniques, together with assessment. Generally the experience has been successful. There have been some problems, mainly organisational and logistical, but the Library and module co-ordinator have resolved these as they arise. However, the recent class size increase, and the possibility that the module may sometime become obligatory, forced the Library to devise an alternative strategy for 2008-09 – a hybrid approach which has enabled the Library to combine new technological options with traditional face-to-face engagement. There are many elements to the new programme, all designed to inform students on content, test the process and obtain feedback. This paper will assess the progress of Library input into the module. It will consider the key nature of relationships with academics, how organisation of the Library content element has been managed over time, and evaluate student response based on diverse evidence derived from online assessment, class feedback and survey. It will examine how developments to date feed into communication with faculty and into future improvements in information literacy development. Finally, the paper will address how Library input has advanced the delivery of information literacy to business undergraduates as a whole, and consider whether libraries should actually invest more in online delivery of information literacy or keep the focus on face-to-face delivery to groups

Stratification Trees for Adaptive Randomization in Randomized Controlled Trials

This paper proposes an adaptive randomization procedure for two-stage randomized controlled trials. The method uses data from a first-wave experiment in order to determine how to stratify in a second wave of the experiment, where the objective is to minimize the variance of an estimator for the average treatment effect (ATE). We consider selection from a class of stratified randomization procedures which we call stratification trees: these are procedures whose strata can be represented as decision trees, with differing treatment assignment probabilities across strata. By using the first wave to estimate a stratification tree, we simultaneously select which covariates to use for stratification, how to stratify over these covariates, as well as the assignment probabilities within these strata. Our main result shows that using this randomization procedure with an appropriate estimator results in an asymptotic variance which is minimal in the class of stratification trees. Moreover, the results we present are able to accommodate a large class of assignment mechanisms within strata, including stratified block randomization. In a simulation study, we find that our method, paired with an appropriate cross-validation procedure ,can improve on ad-hoc choices of stratification. We conclude by applying our method to the study in Karlan and Wood (2017), where we estimate stratification trees using the first wave of their experiment

Unit of instruction.

Thesis (M.A.)--Boston Universit

Boy meets goal, boy loses goal, boy gets goal : the nature of feedback between goal-based simulation and understanding systems

We are designing a goal-based planning and simulation system called REACTOR for a multiple-actor world in which partially formulated plans are monitored during execution, providing feedback to the planner. Plan failures that occur are diagnosed by a combination of top-down (plan-synthesis) and bottom-up (plan-understanding) techniques, allowing an informed choice of response to the error. By maintaining separate belief spaces for each actor, we simulate planners who themselves simulate the planning and plan-understanding of other actors