Using student feedback to improve teaching

Gathering student feedback on teaching practice is commonly used in educational settings as an improvement tool and performance measure. Typically this feedback is collected using rating style surveys when a subject concludes; however, whether this practice improves the quality of teaching requires further research. This study was designed using an action research methodology to investigate the impact of student feedback on teacher practices in a secondary setting. Specifically, the efficacy of an ongoing, collaborative feedback model in which teachers collected student feedback regularly, were guided in reflecting on the data, and were supported through professional development to improve their practices was explored. Results supported student feedback as a valuable improvement tool, and powerful stimulus for teacher reflection. Student feedback informed teachers on the effectiveness of their practice and identified areas for future professional learning. Additionally, it opened up a dialogue around teaching and learning in the classroom, and gave the teachers insights into the unique challenges experienced by their students.     

Using screen capture feedback to improve academic performance

Feedback is an effective instructional practice for improving achievement. The importance of feedback has been understood by teachers for many years, yet recent research has elevated its status. One characteristic of effective feedback is personalized comments, which assist students in understanding their performance. Most research analyzes the effects of written feedback. Some current studies have examined the effects of alternative delivery methods, such as audio. One new approach for creating and delivering feedback is through screen capture technology. A case study was conducted to examine the effects of this method on the academic performance of 36 undergraduate students in a teacher education course. Results showed that screen capture feedback is effective for guiding corrections on a writing assignment. Students also reported that feedback was useful for knowing what they were doing right or wrong and that they would prefer more feedback of this type.     

Using pictorial mnemonics in the learning of tax: a cognitive load perspective

The scope and complexity of the Australian taxation system (as with other tax regimes) is daunting for many accounting students. This paper documents the implementation of new practices that were initiated in an effort to address some of the challenges faced by undergraduate students studying taxation. Based on the principles of cognitive load theory, summaries of the lecture material became the focus of tutorials. These summaries provided the impetus for teaching staff to experiment with illustrations as a strategic means of delivery. Drawing diagrams and presenting them in the form of pictorial mnemonics proved to be effective tools in helping students understand and synthesize basic taxation concepts, thereby promoting effective deep learning. Both formal and informal feedback was overwhelmingly positive and affirming of this innovative approach to the subject. A selection of the pictorial mnemonics we designed is provided.     

Using stakeholder feedback to improve online professional development opportunities

Abstract

Traditional professional development is often characterized as being expensive, time consuming, and lacking impact. In contrast, online professional development provides greater flexibility and is becoming increasingly popular for school personnel. In this article, we report the process and outcomes of gathering feedback to adapt traditional in-person to online training differentiated for the participants to maximize utility, efficiency, and effectiveness in meeting the needs of key stakeholders. Focus groups were conducted with teachers, administrators, and other specialists to gather feedback on content as well as how online learning modules (OLMs) could be tailored to meet specific school site and team needs. We discuss our findings in the context of continuing efforts to improve general and specific professional development opportunities.     

E-learning and technologies for open distance learning in Management Accounting

This research develops a knowledge acquisition and construction framework for e-learning for Management Accounting students at the University of South Africa, an Open Distance Learning institution which utilises e-learning. E-learning refers to the use of electronic applications and processes for learning, including the transfer of skills and knowledge over a distance. It is important to the knowledge construction process to understand how students learn in order to determine a set of suitable learning strategies. Studies have shown that e-learning applications are seldom used, sometimes because of inappropriate content and technologies. Other prohibitive factors are cost, poor or inadequate technology infrastructure (or a lack of access to such infrastructure), and a shortage of human resources. We propose a framework for addressing these concerns and consider how constructivist theories may enrich such a framework.     

Using contrasting cases to improve self-assessment in physics learning

Self-assessment is essential to scientific literacy as stated by the National Research Council Committee on Conceptual Framework for the New K-12 Science Education Standards and has since been incorporated into the Next Generation Science Standards. However, little empirical evidence documents which instructional tools are beneficial in improving students’ self-assessment in science learning. As such, we conducted a classroom-based quasi-experiment to test whether contrasting case-based instructional supports improved 390 introductory high school physics students’ accuracy in self-assessment and academic performance when solving physics problems. We compared the effects of providing students with content knowledge and contrasting cases (contrasting good and poor solution) on students’ physics problem solving and their ability to self-assess, with the effects of either presenting them with content knowledge and good solutions or teaching only content knowledge. We found contrasting examples improved the accuracy of students’ self-assessments, promoted content learning, and enhanced the development of self-assessment strategies.     

浅谈巧用信息技术提高幼儿学习效率

信息技术对当代生活有着重大的影响,在这以多媒体计算机技术和网络通讯技术为标志的时代,信息技术改变着我们的学习方式、生活方式、工作方式。在幼儿教育中,信息技术的运用就是指把文本、图形、图像、声音、影像等经过处理后融合为一体,它的特点是运行的实时生动。在现今时代信息技术已快速融入教学领域,为提高教学质量促进国际教育业的发展打下坚实的基础。     

远程教育网上教学反馈信息的分析与应用

本文应用控制论、信息科学、应用数学与教学系统设计等方法,探讨了信息化环境下的远程教育网上教学信息的分析与应用问题。首先,设立了网上教学反馈信息的定量描述函数,应用这些函数可以从多个维度去描述典型的网上学习行为。其次,基于动力系统稳定性理论建立了判断教学目标发生偏差的定量比较方法。第三,应用数据挖掘的方法,构建了学习行为规律的两个模型。第四,提出了一个把反馈信息应用到教学过程的调节与优化之中的应用模型,分析比较了该模型与一般传统的教学设计模型的特征差异。最后,以典型的实际案例说明了如何应用反馈信息来进行补偿教学。     

Using blended learning to increase learner support and improve retention

Improving retention and identifying ‘at risk’ learners are high profile issues in higher education, and a proposed solution is to provide good learner support. Blending of online learning with classroom sessions offers the potential to use a virtual learning environment to deliver learning activities, and to support learners using a distance learning model. Online tracking can also help to target ‘at risk’ learners quickly. In an action research project to improve retention, a blended module with proactive tutor support was compared with a previous cohort of the module and with similar classroom-only modules where there was no focus on learner support. Learners were also interviewed and the tutor kept records of the learner contact time. The resulting improved coursework submission rate was attributed to learner motivation as a result of peer and tutor support. The total teaching time was no greater in this model, although the workload distribution changed, and the tutor needed to be highly skilled in e-learning.     

Multimodal learning analytics to investigate cognitive load during online problem solving

To have insight into cognitive load (CL) during online complex problem solving, this study aimed at measuring CL through physiological data. This study experimentally manipulated intrinsic and extraneous load of exercises in the domain of statistics, resulting in four conditions: high complex with hints, low complex with hints, high complex without hints and low complex without hints. The study had a within-subject-design in which 67 students solved the exercises in a randomized order. Self-reported CL was combined with physiological data, namely, galvanic skin response (GSR), skin temperature (ST), heart rate (HR) and heart rate variability (HRV). Multiple imputation was used for handling missing data from resp. 16 and 19 students for GSR/ST and HR/HRV. First, differences between conditions in view of physiological data were examined. Second, we investigated how much variance of self-reported CL and task performance was explained by physiological data. Finally, we investigated which features can be used to assess (objective) CL. Results revealed no significant differences between the manipulated conditions in terms of physiological data. Nonetheless, HR and ST were significantly related to self-reported CL, whereas ST to task performance. Additionally, this study revealed the potential of ST and HR to assess high CL.     

Relationships between motivational strategies and cognitive learning in distance education courses

This study examines the relationships between students’ academic levels, the use of motivational regulation strategies, and cognitive learning strategies. A total of 141 undergraduate and graduate students enrolled in online distance courses participated in the study. The findings show that students use different motivational regulation strategies and cognitive learning strategies depending on their academic levels. Additionally, hierarchical regression analyses using two dependent variables (i.e., surface level learning strategy and deep processing level learning strategy) indicate that a surface level learning strategy (i.e., rehearsal) and deep processing level strategies (i.e., elaboration, organization, and critical thinking) are predicted by different sets of motivational regulation strategies after controlling for academic level and age. The results provide distance educators and instructional designers with practical suggestions on how to support undergraduate and graduate students’ motivational needs and further promote their use of cognitive learning strategies in online distance education programs in higher education.     

Activity-based learning of statistics: Using practical applications to improve students' learning

Many obstacles are involved in teaching statistics to undergraduates, including high attrition rates, students' anxiety, and a limited ability to grasp difficult concepts. These concerns can be addressed effectively by implementing strategies that require students to be actively engaged in the learning of statistics. First, we discuss how activity-based strategies and information technology can be an effective way to teach a statistics course. Second, we discuss how we changed a statistics course to include activity-based strategies. Finally, we discuss how cooperative learning, as a type of activity-based strategy, can increase students' understanding of statistics.     

Using learning analytics to scale the provision of personalised feedback

There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this impediment. As students interact with the various learning technologies in their course of study, they create digital traces that can be captured and analysed. These digital traces form the new kind of data that are frequently used in learning analytics to develop actionable recommendations that can support student learning. This paper explores the use of such analytics to address the challenges impeding the capacity of instructors to provide personalised feedback at scale. The case study reported in the paper showed how the approach was associated with a positive impact on student perception of feedback quality and on academic achievement. The study was conducted with first year undergraduate engineering students enrolled in a computer systems course with a blended learning design across three consecutive years (N₂₀₁₃ = 290, N₂₀₁₄ = 316 and N₂₀₁₅ = 415).     

Using achievement goal-based personalized motivational feedback to enhance online learning

Current online learning approaches are sometimes criticized for a “one- size- fits -all” approach and insufficient feedback, which may result in low levels of satisfaction and high dropout rates. To mitigate these shortcomings, we implemented a set of principles for designing personalized motivational feedback based on students’ achievement goals. A sequential explanatory mixed-methods design was used to collect data. The results indicated students who received this feedback demonstrated significantly higher levels of motivation and satisfaction. However, their performance scores were not significantly higher than students in the control group. Post-interviews showed this personalized feedback helped students regulate their learning goals and behaviors and thus improved their learning. The evidence suggests this personalized feedback may benefit learning by improving motivation. While its effect on performance outcomes was not significant, we speculate that more complex factors may have obscured any performance effect.

     

Using technology to facilitate effective assessment for learning and feedback in higher education

The aims of this paper are to examine and critically evaluate a selection of different technological methods that were specifically chosen for their alignment with, and potential to enhance, extant assessment for learning practice. The underpinning perspectives are that: (a) both formative and summative assessment are valuable opportunities for learning, and (b) using technology may enhance learning in assessment and feedback processes. Drawing on the literature and empirical evidence from a research study in a Scottish university, the advantages and drawbacks of using technology are examined. It is asserted that, by adopting a flexible approach and taking small incremental steps, the use of different types of technology can be beneficial in facilitating effective assessment for learning and feedback in higher education.     

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40?years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts.