Marking and providing feedback face-to-face: staff and student perspectives.

The setting, marking and providing feedback on assessments forms an important part of a tutor’s role. Studies into the use of feedback and how it is interpreted by students indicate a mismatch between what students are looking for and what tutors think they are giving. Tutors comment that students are more interested in the mark than the feedback, and yet students indicate that they do not get enough feedback, or that it is not useful. This study investigates student and staff perceptions of the linking of marking and feedback in face-to-face sessions. A cohort of year one university students were given the option of receiving either written feedback or a 15 minute meeting with one of their tutors to have their essay marked with them. Forty nine students chose face-to-face marking, the remaining 35 students received written feedback. Focus groups were used to investigate the student experience. Staff members were also asked to reflect on the process. Students and staff found the experience of face-to-face marking beneficial and positive. Both felt that the time spent together allowed for a feedback dialogue about the piece of work, and that staff could explain and justify why marks were given.

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.

Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operations of pumps. Schedules can be defined either implicitly, in terms of other elements of the network such as tank levels, or explicitly by specifying the time during which each pump is on/off. The traditional representation of explicit schedules is a string of binary values with each bit representing pump on/off status during a particular time interval. In this paper, we formally define and analyze two new explicit representations based on time-controlled triggers, where the maximum number of pump switches is established beforehand and the schedule may contain less switches than the maximum. In these representations, a pump schedule is divided into a series of integers with each integer representing the number of hours for which a pump is active/inactive. This reduces the number of potential schedules compared to the binary representation, and allows the algorithm to operate on the feasible region of the search space. We propose evolutionary operators for these two new representations. The new representations and their corresponding operations are compared with the two most-used representations in pump scheduling, namely, binary representation and level-controlled triggers. A detailed statistical analysis of the results indicates which parameters have the greatest effect on the performance of evolutionary algorithms. The empirical results show that an evolutionary algorithm using the proposed representations improves over the results obtained by a recent state-of-the-art Hybrid Genetic Algorithm for pump scheduling using level-controlled triggers.