Andreas Puder, Moritz Zink, Luca Seidel, Eric Sax
Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models
Sensors (Basel, Switzerland)
research investigated impact planning time working memory wm cognitive styles language learning outcomes within framework taskbased language teaching tblt drawing diverse sample language learners study employed pretestposttest control group quasiexperiment examine effects providing pretask planning time language performance participants engaged communicative tasks focus vocabulary acquisition task complexity cognitive processes assessed measures wm cognitive styles findings revealed significant interactions planning time cognitive styles particularly field dependence influencing language production proficiency learners planning time outperformed learners without planning time highwm learners outperformed lowwm peers field independent learners outstripped fielddependent counterparts moreover study contributes broader understanding nuanced relationship planning time wm cognitive styles context tblt implications findings language teachers materials developers syllabus designers curriculum developers policymakers discussed offering insights design effective language learning environments despite certain limitations study provides foundation research exploring crosscultural variations longitudinal effects integration technology language education aim advancing pedagogical practices tailored diverse learner profiles