Developing expertise is essential to improving pupil outcomes. Teachers’ engagement with education research has seen a significant increase over recent years – which is long overdue and very much needed.
Each week, I will post a research paper on a particular theme linked to developing Expert Teaching, covering several sub-categories of the main theme.
The first #ExpertTeaching research paper comes from Agarwal et al (2017) and focuses on the benefits of retrieval practice.
ABSTRACT:
We examined the effects of retrieval practice for students who varied in working memory capacity as a function of the lag between study of material and its initial test, whether or not feedback was given after the test, and the retention interval of the final test. We sought to determine whether a blend of these conditions exists that maximises benefits from retrieval practice for lower and higher working memory capacity students. College students learned general knowledge facts and then restudied the facts or were tested on them (with or without feedback) at lags of 0–9 intervening items. Final cued recall performance was better for tested items than for restudied items after both 10 minutes and 2 days, particularly for longer study–test lags. Furthermore, on the 2-day delayed test the benefits from retrieval practice with feedback were significantly greater for students with lower working memory capacity than for students with higher working memory capacity (r = −.42). Retrieval practice may be an especially effective learning strategy for lower ability students.
This week’s #ExpertTeaching research paper is from Benjamin and Tullis (2010) and poses the question ‘What makes distributed practice effective?”
ABSTRACT:
The advantages provided to memory by the distribution of multiple practice or study opportunities are among the most powerful effects in memory research. In this paper, we critically review the class of theories that presume contextual or encoding variability as the sole basis for the advantages of distributed practice, and recommend an alternative approach based on the idea that some study events remind learners of other study events. Encoding variability theory encounters serious challenges in two important phenomena that we review here: superadditivity and nonmonotonicity. The bottleneck in such theories lies in the assumption that mnemonic benefits arise from the increasing independence, rather than interdependence, of study opportunities. The reminding model accounts for many basic results in the literature on distributed practice, readily handles data that are problematic for encoding variability theories, including superadditivity and nonmonotonicity, and provides a unified theoretical framework for understanding the effects of repetition and the effects of associative relationships on memory.
This week’s #ExpertTeaching research paper is a hefty one from Bjork & Bjork (1992) and focuses on memory. This is a signficant development from Ebinhaus’ research on The Forgetting Curve.
ABSTRACT:
Speakers at the William K. Estes Symposium at Harvard University were asked to pick, if possible, a research topic where they could trace the influence of W. K. Estes in the work to be reported at the symposium. In the first author’s case, that did not narrow down the possible topics in any substantial way. The work that seemed most timely to report at the symposium, however-the collaborative effort we refer to herein as a “new theory of disuse”-seemed not to be a particularly good example of the various significant influences William K. Estes has had on the two of us. Upon reflection, however, certain formal aspects of our theory correspond to a version of Estes’ stimulus sampling theory, a version that incorporates what we consider to be one of the great insights in the history of research on learning and memory. That insight, initially reported in two short papers in the 1955 volume of the Psychological Review (Estes, 1955a, 1955b), is implemented in the so-called stimulus fluctuation version of Estes’ statistical theory of learning.
However delayed and unconscious the influences may have been, we feel that our new theory of disuse owes some of its features to Estes’ theory of stimulus fluctuation. One goal of this chapter is to sketch the similarities and differences between our theory-of-disuse framework and Estes’ fluctuation model. In the sections that follow, we first summarize the characteristics of human memory that we feel suggest the storage and retrieval properties we postulate in our theory of disuse. We then present that framework along with some of its predictions and some arguments why such a pattern of storage and retrieval characteristics might be, overall, adaptive. We conclude with a section in which we first describe and pay homage to Estes’ stimulus fluctuation insight, and we then compare and contrast the fluctuation model and our theory of disuse.
This week’s #ExpertTeaching research paper is from Dunlosky et. al. (2013) and focuses on improving students’ learning with effective learning techniques: promising directions from cognitive science and education psychology.
SUMMARY:
Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility.We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work.The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice.
To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension.
We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections:
1. General description of the technique and why it should work
2. How general are the effects of this technique?
2a. Learning conditions 2b. Student characteristics 2c. Materials
2d. Criterion tasks
3. Effects in representative educational contexts
4. Issues for implementation
5. Overall assessment
The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques.
To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students’ performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self- explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique.
Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading.These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness.The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students’ performance, so other techniques should be used in their place (e.g., practice testing instead of rereading).
Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research.
This week’s #ExpertTeaching research paper is from Soderstrom and Bjork (2015) and reviews the difference between learning and performance.
ABSTRACT:
The primary goal of instruction should be to facilitate long-term learning—that is, to create relatively permanent changes in comprehension, understanding, and skills of the types that will support long-term retention and transfer. During the instruction or training process, however, what we can observe and measure is performance, which is often an unreliable index of whether the relatively long-term changes that constitute learning have taken place. The time- honored distinction between learning and performance dates back decades, spurred by early animal and motor-skills research that revealed that learning can occur even when no discernible changes in performance are observed. More recently, the converse has also been shown—specifically, that improvements in performance can fail to yield significant learning—and, in fact, that certain manipulations can have opposite effects on learning and performance. We review the extant literature in the motor- and verbal-learning domains that necessitates the distinction between learning and performance. In addition, we examine research in metacognition that suggests that people often mistakenly interpret their performance during acquisition as a reliable guide to long-term learning. These and other considerations suggest that the learning–performance distinction is critical and has vast practical and theoretical implications.
This week’s #ExpertTeaching research paper is from Matthew G. Rhodes (2016) and reviews our judgements of learning: methods, data and theory.
ABSTRACT:
Several decades of research have examined predictions of future memory performance— typically referred to as judgments of learning (JOLs). In this chapter, I first discuss the early history of research on JOLs and their fit within a leading metacognitive framework. A common methodological approach has evolved that permits the researcher to investigate the correspondence between JOLs and memory performance, as well as the degree to which JOLs distinguish between information that is or is not remembered. Factors that influence each aspect of the accuracy of JOLs are noted and considered within theoretical approaches to JOLs. Thus far, research on JOLs had yielded a number of findings and promising theoretical frameworks that will continue to be refined. Future work will benefit by considering how learners combine information to arrive at a judgment, the implications of alternative methods of measuring JOLs, and the potential for JOLs to influence memory.
This week’s #ExpertTeaching research paper is from Dylan Wiliam (2004) and discusses teachers themselves developing assessment for learning and its impact on student achievement.
ABSTRACT:
While it is generally acknowledged that increased use of formative assessment (or assessment for learning) leads to higher quality learning, it is often claimed that the pressure in schools to improve the results achieved by students in externally-set tests and examinations precludes its use.
This paper reports on the achievement of secondary school students who worked in classrooms where teachers made time to develop formative assessment strategies. A total of 24 teachers (2 science and 2 mathematics teachers, in each of six schools in two LEAs) were supported over a six-month period in exploring and planning their approach to formative assessment, and then, beginning in September 1999, the teachers put these plans into action with selected classes. In order to compute effect sizes, a measure of prior attainment and at least one comparison group was established for each class (typically either an equivalent class taught in the previous year by the same teacher, or a parallel class taught by another teacher). The mean effect size in favour of the intervention was 0.32.
This week’s #ExpertTeaching research paper is another from Dylan Wiliam (2011) and discusses the definitions and relationships of formative assessment.
ABSTRACT:
The idea that assessment is intrinsic to effective instruction is traced from early experiments in the individualization of learning through the work of Benjamin Bloom to reviews of the impact of feedback on learners in classrooms. While many of these reviews detailed the adverse impact of assessment on learning, they also indicated that under certain conditions assessment had considerable potential to enhance learning. It is shown that understanding the impact that assessment has on learning requires a broader focus than the feedback intervention itself, particularly the learner‟s responses to the feedback, and the learning milieu in which the feedback operates. Different definitions of the terms “formative assessment” and “assessment for learning” are discussed, and subsumed within a broad definition that focuses on the extent to which instructional decisions are supported by evidence. The paper concludes by exploring some of the consequences of this definition for classroom practice.
This week’s #ExpertTeaching research paper is from DeLuca et. al., (2012) on the barriers to implementation and possibilities for teacher professional learning with regards to assessment for learning in the classroom.
ABSTRACT:
Assessment for learning (AfL) has been touted as one of the most promising pedagogical approaches for enhancing student learning.
Research suggests that engaging students in AfL helps to improve their achievement, develop metacognition and support motivated learning and positive self-perceptions. However, despite these promises, there have been notable barriers impeding teachers’ use of AfL in their classrooms. Time and class sizes; conceptual confusions related to AfL; perceived misalignment between system priorities and classroom assessment practices; and a lack of effective models for professional development on assessment have all been cited as critical challenges in promoting the implementation of AfL in classrooms.
Given these challenges, in this paper we ask: What would it take to make AfL integration possible and practical within the current context of education? In response to this question, we assert the benefits of using contemporary approaches to teacher professional learning that explicitly address gaps and challenges in AfL implementation. Further, we provide grounding for a programme of research in developing teachers’ assessment capacity by first summarising challenges to the integration of AfL and then exploring potential directions for professional learning in this area.
This week’s #ExpertTeaching research paper – and the final in the assessment series – is from Heitink et. al. and focuses on “A systematic review of prerequisites for implementing assessment for learning in classroom practice.”
ABSTRACT:
Although many researchers acknowledge that Assessment for Learning can significantly enhance student learning, the factors facilitating or hindering its implementation in daily classroom practice are unclear. A systematic literature review was conducted to reveal prerequisites needed for Assessment for Learning implementation. Results identified prerequisites regarding the teacher, student, assessment and context.
For example, teachers must be able to interpret assessment information on the spot, student engagement in the assessment process is vital, assessment should include substantial, constructive and focussed feedback, and the school should have a school-wide culture that facilitates collaboration and encourages teacher autonomy. The results of this review contribute to a better understanding of the multiple facets that need to be considered when implementing Assessment for Learning, from both a theoretical and a practical standpoint.