Spaced retrieval is a memory-training technique whereby information is tested at progressively longer delays. Two experiments were conducted to examine effects of spaced retrieval on controlled recollection and automatic influences of memory. In Experiment 1, word-pairs were read once, read three times, or read once and retrieved twice by young and older adults. Retrieval practice improved perf...

Introduction 1 A Primer on Retrieval-Based Learning 2 Direct Versus Mediated Effects of Retrieval Practice 2 Balancing Retrieval Success and Retrieval Effort 4 Theories of Retrieval-Based Learning 5 Transfer-Appropriate Processing 5 Strength and Retrieval Effort 5 Elaborative Retrieval Account 6 Episodic Context Account 7 Manipulations of Initial Retrieval Practice Conditions 7 Retrieval Practi...

The science of learning has made a considerable contribution to our understanding of effective teaching and learning strategies. However, few instructors outside of the field are privy to this research. In this tutorial review, we focus on six specific cognitive strategies that have received robust support from decades of research: spaced practice, interleaving, retrieval practice, elaboration,...

Introduction: In the test-enhanced spaced learning, educationalcontents are presented in small packages of well-developedtest questions with a defined frequency to the learners. It is notclear that applying this educational style might have a positiveimpact on the summative assessment. Therefore, in this studywe assessed the effect of the test-enhanced spaced learn...

Spaced seed is a filter method invented to efficiently identify the regions of interest in similarity searches. It is now well known that certain spaced seeds hit (detect) a randomly sampled similarity region with higher probabilities than the others. Assume each position of the similarity region is identity with probability p independently. The seed optimization problem seeks for the optimal s...

SAlthough different theoretical models are complementary, functional models in general, andSystemic Functional Linguistics in particular lend themselves to the analysis of text. This is so atthe level of register, in terms of Field, Tenor and Mode, as well as at the level of semantics interms of ideational, interpersonal and textual metafunction. This paper will consider two...

Many methods have been developed for spectral analysis of irregularly sampled data. Currently, popular methods such as Lomb–Scargle and resampling tend to be biased at higher frequencies. Slotting methods fail to consistently produce a spectrum that is positive for all frequencies. In this paper, a new estimator is introduced that applies the Burg algorithm for autoregressive spectral estimatio...