Retrieval-, Distributed-, and Interleaved Practice in the Classroom:A Systematic Review

Three of the most effective learning strategies identified are retrieval practice, distributed practice, and interleaved practice, also referred to as desirable difficulties. However, it is yet unknown to what extent these three practices foster learning in primary and secondary education classrooms (as opposed to the laboratory and/or tertiary education classrooms, where most research is conducted) and whether these strategies affect different students differently. To address these gaps, we conducted a systematic review. Initial and detailed screening of 869 documents found in a threefold search resulted in a pool of 29 journal articles published from 2006 through June 2020. Seventy-five effect sizes nested in 47 experiments nested in 29 documents were included in the review. Retrieval- and interleaved practice appeared to benefit students’ learning outcomes quite consistently; distributed practice less so. Furthermore, only cognitive Student*Task characteristics (i.e., features of the student’s cognition regarding the task, such as initial success) appeared to be significant moderators. We conclude that future research further conceptualising and operationalising initial effort is required, as is a differentiated approach to implementing desirable difficulties

Argumentation, Ideology and Discourse in Evolving Specialized Communication

In the digital age, the transformation process of information into ‘knowledge’ is characterized by hyper-connected communities, where a potentially infinite amount of information is ubiquitously accessible to individuals or community users and is instrumental in the creation of shared knowledge, but also in building consensus across community participants, societal membership and grouping, through the argumentative ideological representation of assumptions, values and practices. This Special Issue of “Lingue e Linguaggi” on the theme Argumentation, Ideology and Discourse in Evolving Specialized Communication explores the interface between these three dimensions and combines an array of perspectives into a distinctly unified volume, offering synchronic, diachronic, comparative, interlinguistic and intercultural approaches over a range of specialized knowledge domains. The volume integrates quantitative and qualitative approaches, making use of Corpus Linguistics, alongside other methods incorporated in theoretical approaches such as Critical Discourse Analysis, Appraisal Theory and Argumentation Theory, focusing on the pragma-linguistic features of different texts and genres, together with their ideological purposes for different audiences in various contexts of use. The collection of essays investigates argumentative styles and patterning along with the discursive socio-construction of ideology in the dynamics of recontextualization, rescripting and remediation which affect the multi-faceted nature of contemporary communication

Building a Call to Action: Social Action in Networks of Practice

The three research papers completed as part of this dissertation explore how people contributing to #BlackLivesMatter build knowledge, using social construction of knowledge (SCK), and what they are building knowledge about, using critical consciousness, because understanding how these processes play out on Twitter provides a way for others to understand this social movement. Paper 1 describes a new methodological approach to combining social network analysis (SNA) and social learning analytics to assess SCK. The sequential mixed method design begins by conducting a content analysis according to the Interaction Analysis Model (IAM). The results of the content analysis yield descriptive data that can be used to conduct SNA and social learning analytics. The purpose of Paper 2 was to use the typology of digital activism actions identified by Penney and Dadas (2014) from interviews with digital activists to validate them in a quantitative study. Paper 2 found that the actions taken by people who are helping to facilitate face-to-face action (p \u3c .0000001 , r = -0.076) or provide face-to-face updates (p \u3c .0000001 , r = -0.060) were negatively correlated with the actions of people who were facilitating online actions suggesting that digital activists should be treated as a unique population of activists. Paper 3 used the outcomes of a content analysis and lexicon analysis performed on #BlackLivesMatter data to determine 1) the levels of SCK and critical consciousness present in online data and 2) social learning analytics to ascertain the extent that SCK and critical consciousness can predict social action. Results of the content analysis and lexicon analysis found all levels of SCK and critical consciousness in the data. Results of social learning analytics conducted using Naïve Bayes classification indicate that SCK and critical consciousness can only predict information sharing behaviors of online social action like personal opinions, forwarding information, and engaging in discussion. Evidence of information sharing behaviors on Twitter provides a high degree of confidence that further research including replies and other interactions between users will reveal robust SCK