Explore the vast range of titles available.

In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate students in a context similar to what a poem describes. In addition, the progressive prompt is a strategy that can progressively provide students with clues and guidance in technology-enhanced learning environments. Hence, this study proposed a progressive prompts-based image-GAI (PP-iGAI) approach to support students' ancient Chinese poetry learning. To evaluate its effectiveness, the present study employed a quasi-experiment design and recruited 80 fifth-grade elementary school students to engage in one of two conditions: one class was assigned as the experimental group and adopted the PP-iGAI approach, while the other class was assigned as the control group and used the conventional prompt-based iGAI (C-iGAI) approach. The results revealed that the PP-iGAI approach could better promote students' learning achievement, extrinsic motivation, problem-solving awareness, critical thinking, and learning performance. In addition, no significant differences were found in the two groups' cognitive load. Moreover, the results of the interview disclosed the learning perceptions and experiences of both groups. Accordingly, the present study can provide a reference not only for ancient Chinese poetry learning but also for the application of GAI in educational fields for future research.

We examined the effectiveness and efficiency of 2 instructional arrangements using progressive prompt delay (PPD) with 3 young children with autism and 1 child with developmental delays. Specifically, we compared PPD with instructive feedback (IF) to PPD without IF in an adapted alternating treatment design. The results suggested that (a) children with autism and developmental delays can learn when PPD is used with IF, (b) IF can be an effective method of instruction for young children with autism and developmental delays, and (c) the combination of PPD and IF can increase the efficiency of instruction. Data collected 8 to 9 weeks after instruction ended showed that participants maintained mastery of 58% to 92% of the acquired behaviors. We discuss these results within the constraints and limitations of the data and recommend areas for future research.

The current two-experiment study examined the effects of a regressive prompt-delay procedure on sight-word reading of four elementary school students. In contrast to traditional progressive prompt-delay procedures in which the latency of prompts is increased, the regressive prompt-delay latency is decreased over time. Data indicate that participants learned sight words quickly and maintained responding at high levels when instruction was withdrawn across both regressive and progressive prompt-delay conditions. Results are discussed in context of empirically supported prompting strategies and possible motivating operations that might be introduced when the learner is instructed to respond more quickly than the experimenter in regressive prompt delay (e.g., a game-like activity that potentially makes the activity educational, engaging, and enjoyable for students).

With the continuous advancement of deep neural networks, salient object detection (SOD) in natural images has made significant progress. However, SOD in optical remote sensing images (ORSI-SOD) remains a challenging task due to the diversity of objects and the complexity of backgrounds. The primary challenge lies in generating robust features that can effectively integrate both global semantic information for salient object localization and local spatial details for boundary reconstruction. Most existing ORSI-SOD methods rely on pre-trained CNN- or Transformer-based backbones to extract features from ORSIs, followed by multi-level feature aggregation. Given the significant differences between ORSIs and the natural images used in pre-training, the generalization capability of these backbone networks is often limited, resulting in suboptimal performance. Recently, prompt engineering has been employed to enhance the generalization ability of networks in the Segment Anything Model (SAM), an emerging vision foundation model that has achieved remarkable success across various tasks. Despite its success, directly applying the SAM to ORSI-SOD without prompts from manual interaction remains unsatisfactory. In this paper, we propose a novel progressive self-prompting model based on the SAM, termed PSP-SAM, which generates both internal and external prompts to enhance the network and overcome the limitations of SAM in ORSI-SOD. Specifically, domain-specific prompting modules, consisting of both block-shared and block-specific adapters, are integrated into the network to learn domain-specific visual prompts within the backbone, facilitating its adaptation to ORSI-SOD. Furthermore, we introduce a progressive self-prompting decoder module that performs prompt-guided multi-level feature integration and generates stage-wise mask prompts progressively, enabling the prompt-based mask decoders outside the backbone to predict saliency maps in a coarse-to-fine manner. The entire network is trained end-to-end with parameter-efficient fine-tuning. Extensive experiments on three benchmark ORSI-SOD datasets demonstrate that our proposed network achieves state-of-the-art performance.

We examined the controlling factors that allow a prompted skill to become autonomous in a discrete-trials implementation of Touchette’s (1971) progressively delayed prompting procedure, but our subjects were rats rather than children with disabilities. Our prompted skill was a left-right lever-press sequence guided by two panel lights. We manipulated (a) the effectiveness of the guiding lights prompt and (b) the presence or absence of a progressively delayed prompt in four groups of rats. The less effective prompt yielded greater autonomy than the more effective prompt. The ability of the progressively delayed prompt procedure to produce behavioral autonomy depended upon characteristics of the obtained delay (trial duration) rather than on the pending prompt. Sequence accuracy was reliably higher in unprompted trials than in prompted trials, and this difference was maintained in the 2 groups that received no prompts but yielded equivalent trial durations. Overall sequence accuracy decreased systematically as trial duration increased. Shorter trials and their greater accuracy were correlated with higher overall reinforcement rates for faster responding. Waiting for delayed prompts (even if no actual prompt was provided) was associated with lower overall reinforcement rate by decreasing accuracy and by lengthening trials. These findings extend results from previous studies regarding the controlling factors in delayed prompting procedures applied to children with disabilities.