The Effects of Strategy on Monitoring Accuracy

The remote sensing extraction of large areas of arecanut (Areca catechu L.) planting plays an important role in investigating the distribution of arecanut planting area and the subsequent adjustment and optimization of regional planting structures. Satellite imagery has previously been used to investigate and monitor the agricultural and forestry vegetation in Hainan. However, the monitoring accuracy is affected by the cloudy and rainy climate of this region, as well as the high level of land fragmentation. In this paper, we used PlanetScope imagery at a 3 m spatial resolution over the Hainan arecanut planting area to investigate the high-precision extraction of the arecanut planting distribution based on feature space optimization. First, spectral and textural feature variables were selected to form the initial feature space, followed by the implementation of the random forest algorithm to optimize the feature space. Arecanut planting area extraction models based on the support vector machine (SVM), BP neural network (BPNN), and random forest (RF) classification algorithms were then constructed. The overall classification accuracies of the SVM, BPNN, and RF models optimized by the RF features were determined as 74.82%, 83.67%, and 88.30%, with Kappa coefficients of 0.680, 0.795, and 0.853, respectively. The RF model with optimized features exhibited the highest overall classification accuracy and kappa coefficient. The overall accuracy of the SVM, BPNN, and RF models following feature optimization was improved by 3.90%, 7.77%, and 7.45%, respectively, compared with the corresponding unoptimized classification model. The kappa coefficient also improved. The results demonstrate the ability of PlanetScope satellite imagery to extract the planting distribution of arecanut. Furthermore, the RF is proven to effectively optimize the initial feature space, composed of spectral and textural feature variables, further improving the extraction accuracy of the arecanut planting distribution. This work can act as a theoretical and technical reference for the agricultural and forestry industries.

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Exploring the relations between teachers’ cue-utilization, monitoring and regulation of students’ text learning

Metacognition and Learning ◽

10.1007/s11409-021-09268-6 ◽

2021 ◽

Author(s):

Janneke van de Pol ◽

Selia N. van den Boom-Muilenburg ◽

Tamara van Gog

Keyword(s):

Direct Effect ◽

Text Learning ◽

Cue Utilization ◽

Effective Interventions ◽

Monitoring Accuracy ◽

Effect Monitoring ◽

Within Subjects ◽

Learning From Texts ◽

And Performance ◽

Cue Availability

AbstractThis study investigated teachers’ monitoring and regulation of students’ learning from texts. According to the cue-utilization framework (Koriat, in Journal of Experimental Psychology, 126, 349–370, 1997), monitoring accuracy depends on how predictive the information (or cues) that teachers use to make monitoring judgments actually is for students’ performance. Accurate monitoring of students’ comprehension is considered a precondition for adaptive regulation of students’ learning. However, these assumptions have not yet been directly investigated. We therefore examined teachers’ cue-utilization and how it affects their monitoring and regulation accuracy. In a within-subjects design, 21 secondary education teachers made monitoring judgments and regulation decisions for fifteen students under three cue-availability conditions: 1) only student cues (i.e., student’s name), 2) only performance cues (i.e., diagrams students completed about texts they had read), and 3) both student and performance cues (i.e., student’s name and completed diagram). Teachers’ absolute and relative monitoring accuracy was higher when having student cues available in addition to diagram cues. Teachers’ relative regulation accuracy was higher when having only performance cues available instead of only student cues (as indicated by a direct effect). Monitoring accuracy predicted regulation accuracy and in addition to a direct effect, we also found and indirect effect of cue-availability on regulation accuracy (via monitoring accuracy). These results suggest that accurate regulation can be brought about both indirectly by having accurate monitoring judgments and directly by cue-utilization. The findings of this study can help to refine models of teacher monitoring and regulation and can be useful in designing effective interventions to promote teachers’ monitoring and regulation.

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