An investigation of issues in the teaching and management of large classes

In a quest for a more efficient education system, many organizations have opted to increase class size. It is a common perception that large subjects are economical to run and small subjects are not. Many in the tertiary education system have had concerns with issues involved in the teaching of large classes, including teaching quality and whether there are effective learning outcomes for students. As with any complex issue, there are several approaches that could be utilized to assess whether the needs of stakeholders are being met. Stakeholders include the institution, the teaching staff, the community and the students. This study aims to assess whether universities are satisfying the needs of students as class size is increased. The study focuses on satisfaction with large classes and includes an assessment of the satisfaction of students' psychological needs. These constructs are measured in small, medium and large classes to identify the change in the level of satisfaction. The study used a multi-method approach consisting of a literature review, a qualitative phase involving in-depth interviews, focus groups, and a quantitative survey. The results show that while customer satisfaction is being met, the satisfaction of students' psychological needs are not being fully realised. It was also found that there were notable variations between individual students, the subjects being studied and degree streams of students taking the same subject. The implications of these findings and suggestions for further investigation are discussed in this paper.

Small classes 'a must' for unis

Smaller university tutorial class sizes are "a necessity" to increase student participation and maintain high learning standards, an international higher education expert says.

However, it is feared pressure on universities to make "efficiency savings" will prevent student-teacher ratios from improving from what local academics say is worse than in secondary school settings.

Cognitive intervention in autism using multimedia stimulus

We demonstrate an open multimedia-based system for delivering early intervention therapy for autism. Using exible multi-touch interfaces together with principled ways to access rich content and tasks, we show how a syllabus can be translated into stimulus sets for early intervention. Media stimuli are able to be presented agnostic to language and media modality due to a semantic network of concepts and relations that are fundamental to language and cognitive development, which enable stimulus complexity to be adjusted to child performance. Being open, the system is able to assemble enough media stimuli to avoid children over-learning, and is able to be customised to a specific child which aids with engagement. Computer-based delivery enables automation of session logging and reporting, a fundamental and time-consuming part of therapy.

An analysis of student engagement when taught in classes of different sizes in rural, regional and metropolitan campuses of an Australian university

This study investigates the impact of class size on student engagement and student performance. It is based on an analysis of student university enter scores, student grades and student evaluations in metropolitan, regional and rural campuses of an Australian universityduring trimester 1 of years 2008, 9 & 10. Past literature appears to support the predominant influence of the class size effect on learning, though some findings are mixed and inconclusive. Contrary to the accepted view that higher entry level scores result in higher grades and, conversely, lower entry level scores result in lower grades, the findings suggest that factorsother than entry level scores, contribute to student outcomes and student engagement. The study reveals that student satisfaction of teaching quality is higher in the rural and regional campuses where the cohorts are smaller than at the metropolitan campus. This may be an indication that class size seems to have a predominant influence on student engagement and learning outcomes.

A comparison of two methods in acquiring stimulus-response curves with transcranial magnetic stimulation

Background
The stimulus–response (S–R) curve is a well accepted constituent in transcranial magnetic stimulation (TMS) studies. However, it has been suggested that parameters of the S–R curve differ when stimuli are provided in a “ramped” (measured steps from low to high intensity), or “random” fashion.

Hypothesis
We hypothesized that there would be no difference in the parameters of the S–R curve between either methodologies.

Methods
Using a randomised cross-over design, 10 healthy participants (29.6 ± 6.4 yrs, 3 f) completed “ramped” or “random” curves in biceps brachii (BB) and first dorsal interosseous (FDI) muscles of both limbs. Curves were compared using mixed-factor ANOVA and correlated between limbs and methodologies.

Results
No differences (P > 0.05) and high correlations (range 0.71–0.97; P < 0.001) were observed in BB and FDI data between curves.

Conclusions
This study demonstrated that either methodology provides similar parameters of the S–R curve in healthy participants.

Developing leaders of change in the teaching of large university chemistry classes

Final report of the the Active Learning in University Science (ALIUS) project.

This project aims to establish a new direction in first year chemistry teaching – away from didactic teaching methods in large lecture style teaching to more active, student centred learning experiences. Initially six universities have been involved in practice-based innovation: Charles Sturt University (NSW), The University of Sydney (NSW), Curtin University of Technology (WA), The University of Adelaide (SA), Deakin University (Vic), University of Tasmania (Tas).

Three domains have been identified as the architecture upon which sustainable L&T innovation will be built. These domains include Learning and Teaching innovation in project leaders’ and colleagues’ classrooms, development of project leaders as Science Learning Leaders, and creation of a Science Learning Hub to serve as a locus and catalyst for the development of a science teaching community of practice.

Progress against specified outcomes and deliverables

Learning and Teaching Innovation

The purpose of this domain is to improve student learning, engagement, retention and performance in large chemistry classes through increased use of student-centred teaching practice.
• The Project is named: ALIUS (Active Learning in University Science) - Leading Change in Australian Science Teaching
• All six ALIUS universities have now implemented Teaching Innovation into ALIUS team member classrooms
• Chemistry colleagues at three ALIUS universities have now implemented Teaching Innovation into their classrooms
• The ALIUS member in physics has implemented Teaching Innovations into his classrooms
• Chemistry colleagues at three ALIUS institutions have tried some Teaching Innovations in their classrooms
• Non-chemistry colleagues at four ALIUS institutions have tried, or expressed an interest in trying, Teaching Innovations in their classrooms
• The POGIL method has proved to be a useful model for Teaching Innovation in the classroom
• Many classroom resources have been developed and used at several ALIUS institutions; some of these have been submitted to the ALIUS database for public access. The remainder will continue to submitted
• Two seminars about Teaching Innovation have been developed, critiqued, revised, and presented at five ALIUS universities and three non-ALIUS universities
• Particular issues associated with implementing Teaching Innovations in Australian classrooms have been identified and possible solutions developed
• ALIUS members have worked with Learning and Teaching Centres at their universities to share methods.

Developing Science Learning Leaders

The purpose of this domain is to develop leadership capacity in the project leaders to equip them with skills to lead change first at their institutions, followed by developing leaders and leading change at other local institutions
• ALIUS members participated in Leadership Professional Development sessions with Craig McInnis and Colin Mason; both these sessions were found to be valuable and provide context and direction for the members and the ALIUS team
• The passion of an ‘early adopter’ was found to be a significant element in each node of the distributed framework
• Members developed an awareness of the necessity to build both the ‘sense of urgency’ and the ‘guiding coalition’ at each node
• ALIUS found the success of the distributed framework is strongly influenced by the relational aspects of the team.

Create a Science Learning Hub

The online Hub serves as a local and national clearinghouse for development of institutional Learning Leaders and dissemination of L&T innovation.
• The ALIUS website is now active and being populated with resources
• The sharing resource database structure is finalised and being populated with contributed materials.

Lessons Learnt

In order to bring about change in teaching practice it is necessary to:
• demonstrate a convincing benefit to student learning
• show that beyond an initial input of effort classroom innovations will not take more time than what is now done
• maintain a prominent exposure among colleagues - repeatedly give seminars, workshops, and everyday conversations; talk about teaching innovation; talk about easy tools to use; invite people to your classroom; engage colleagues in regular peer review of classroom practice
• have support from people already present in leadership roles to lead change in teaching practice
• have a project leader, someone for whom the project is paramount and will push it forward
• find a project manager, even with money budgeted
• meet face-to-face.

Dissemination
• Seminars presented 19 times including over 400 individuals and more than 24 Australian universities
• Workshops presented 25 times, over 80 participants at 11 Australian and two New Zealand Universities
• Two articles published in Chemistry in Australia, the Australian Chemistry Industry Journal of the Royal Australian Chemical Institute
• One refereed paper published in the Journal of Learning Design.

Cane toad or computer mouse? Real and computer-simulated laboratory exercises in physiology classes

Traditional practical classes in many countries are being rationalised to reduce costs. The challenge for university educators is to provide students with the opportunity to reinforce theoretical concepts by running something other than a traditional practical program. One alternative is to replace wet labs with comparable computer simulations. These virtual experiments involve no harm to animals and require little ongoing expenditure. This study documents second-year physiology students' perceptions of and attitudes to simulations by incorporating several computer simulations into the practical program. Computer simulations met the conceptual and, to some extent, the motivational goals of university practical programs. While students enjoyed both wet labs and computer-simulated exercises, overwhelmingly the wet lab provided the more memorable and stimulating learning experience. Based on this study, students suggested that computer simulations could be effectively used to complement rather than replace practical classes where students gain laboratory skills.

A framework for identifying affinity classes of inorganic materials binding peptide sequences

With the rapid development of bionanotechnology, there has been a growing interest recently in identifying the affinity classes of the inorganic materials binding peptide sequences. However, there are some distinct characteristics of inorganic materials binding sequence data that limit the performance of many widely-used classification methods. In this paper, we propose a novel framework to predict the affinity classes of peptide sequences with respect to an associated inorganic material. We first generate a large set of simulated peptide sequences based on our new amino acid transition matrix, and then the probability of test sequences belonging to a specific affinity class is calculated through solving an objective function. In addition, the objective function is solved through iterative propagation of probability estimates among sequences and sequence clusters. Experimental results on a real inorganic material binding sequence dataset show that the proposed framework is highly effective on identifying the affinity classes of inorganic material binding sequences.