代数应用题项目生成的结构分析方法

自动化项目生成是近年来兴起的测量领域, 是一种以项目认知加工理论为基础的原则性项目设计(principled item design)模式。其中, 如何在项目认知模型基础上, 通过任务结构分析的方式系统全面的鉴别和提取任务特征是一个关键环节。基于已有文献中代数应用题的命题分析法、网络语言分析法、关系-函数分析法、任务分析地图等四种结构分析方法, 研究探索了能够服务于自动化项目生成的代数应用题任务结构分析方法。该分析表明, 前三种方法分别对应于个体解题过程需要形成的三种中介表征, 即问题陈述背后的命题表征、事件时空关系的情境模型、以及变量间数量关系的问题模型, 第四种方法从过程角度分析了问题解决的认知需求。然而, 要实现项目生成的特征提取需求, 尚需对现有四种方法所揭示问题特征的心理现实性、特征提取的系统性和完备性、任务领域的适用范围、以及不同方法的整合等问题开展进一步研究。     

Generating leads with sequential persuasion: should sales influence tactics be consistent or complementary?

Firms are becoming increasingly systematic in sales lead generation activities and recognize that multiple interactions are often required to generate leads and to reassure buyers of the benefits of an offering. However, the literature is contradictory regarding what types of persuasive messages should be used across these multiple interactions. This paper investigates what combination of sales influence tactics (SITs) should be used when customers are approached more than once regarding the same offering, that is, sequentially. Should the SITs be consistent (the same), or complementary (different)? Consistent vs. complementary SIT approaches were tested in two field experiments, one with an electronics manufacturer in a single communication channel setting and one with a financial services provider in a cross-channel setting. The results supported our hypothesis and indicated that the use of complementary SITs across interactions, regardless of the order, increases lead conversion.     

Destruction and guilt: Splitting and reintegration in the analysis of a traumatised patient

The author traces in detail how, in the analytic relationship, she was slowly able to read aspects of the trauma as 'quotations' and gradually, through transference, transform them into a symbolic language. Split-off aggression and guilt feelings became progressively accessible to interpretation through transferential projective identifi cations. During his analysis, the patient discovered he was the child of Nazi criminals: on his mother's side they were the third generation; on his father's side, the second.     

Building on the ideas of others: An examination of the idea combination process

Two experiments were conducted to explore the process of building on ideas in brainstorming. Although this is presumed to be an important role of brainstorming, this has never been explored experimentally. In one experiment individual and group brainstormers generated ideas which were subsequently presented to these same individuals and groups to combine and build on for additional ideas, either as groups or individuals. The combination process was influenced by whether the participants had previously brainstormed alone or in groups and the phase of the combination period (early vs. late). In a second study participants were presented lists of rare or common ideas to combine and build on either as individuals or groups. Although groups generated fewer combinations than nominal groups, they generated more novel and feasible combinations when combining rare ideas. These findings indicate that groups are able to benefit from the exchange process in building on each other's ideas and are interpreted in the context of past research on idea generation and evaluation in groups.     

Exploring and Promoting the College Attendance and Success of Racial/Ethnic Minority Students

Using consensual qualitative research methodology and being mindful of both challenges and successes, the authors explored diverse students’ experiences with higher education. The authors used semistructured interviews with 7 students with racial/ethnic minority backgrounds to investigate the circumstances under which these students decided to attend college and experienced success. Multiple factors that were reported to contribute to students’ college attendance and success emerged, including individual factors, psychological factors, social factors, and cultural/environmental factors. Utilizando una metodología de investigación cualitativa consensuada y teniendo en cuenta tanto los desafíos como los éxitos, los autores exploraron las experiencias de estudiantes diversos en la educación superior. Los autores usaron entrevistas semiestructuradas con 7 estudiantes de minorías raciales/étnicas para investigar las circunstancias en las que estos estudiantes decidieron cursar estudios universitarios y tuvieron éxito. Surgieron múltiples factores reportados que contribuyeron a la asistencia y al éxito de los estudiantes en la universidad, incluyendo factores individuales, factores psicológicos, factores sociales y factores culturales/del entorno.     

Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architectures

In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures.     

Conceptual blending of high-level features and data-driven salience computation in melodic generation

Conceptual Blending (CB) theory describes the cognitive mechanisms underlying the way humans process the emergence of new conceptual spaces by blending two input spaces. CB theory has been primarily used as a method for interpreting creative artefacts, while recently it has been utilised in the context of computational creativity for algorithmic invention of new concepts. Examples in the domain of music include the employment of CB interpretatively as a tool to explain musical semantic structures based on lyrics of songs or on the relations between body gestures and music structures. Recent work on generative applications of CB has shown that proper low-level representation of the input spaces allows the generation of consistent and sometimes surprising blends. However, blending high-level features (as discussed in the interpretative studies) of music explicitly, is hardly feasible with mere low-level representation of objects. Additionally, selecting features that are more salient in the context of two input spaces and relevant background knowledge and should, thus, be preserved and integrated in new interesting blends has not yet been tackled in a cognitively pertinent manner. The paper at hand proposes a novel approach to generating new material that allows blending high-level features by combining low-level structures, based on statistically computed salience values for each high-level feature extracted from data. The proposed framework is applied to a basic but, at the same time, complicated field of music, namely melodic generation. The examples presented herein allow an insightful examination of what the proposed approach does, revealing new possibilities and prospects.     

The role of the executive system in visuo-spatial memory functioning

Participants were presented with a spatial sequence in which between 4 and 10 cells were highlighted. On each trial list length was unknown to the participant who was required to serially recall the last four cells. Processing of longer lists is assumed to call upon the executive system, which is thought to be involved in updating the contents of the short-term visuo-spatial store. Study 1 revealed that loading the executive system with concurrent random letter generation impaired performance on the spatial task especially recall of the early serial positions. However, contrary to expectation the degree of impairment was no greater on the longer lists, where it had been assumed that updating would be occurring. Study 2 confirmed this finding and demonstrated that relative to sequences of known length, under conditions of uncertainty when the list length was unknown, spatial recall was impaired even on short sequences. The present results support the growing consensus, which is suggestive of closer links between visuo-spatial and executive processes. However, it remains unclear whether or not updating is actually occurring on the longer sequences, and if it is, what specific executive processes are involved.     

Energy management solutions in the Internet of Things applications: Technical analysis and new research directions

By advancement of Internet of Things (IoT) technology in smart life such as smart city, smart home, smart healthcare and smart transportation, interconnections between smart things are growing that complicate evaluation of efficiency factors on the intelligent systems. Energy consumption as one of the most challenging issues is increasing with the growing IoT devices and existing interconnections between cloud data centers, mobile applications and human activities. Managing energy efficiency and power consumption is one of the important issues in green IoT-enabled technologies. This paper presents an overview on the energy management solutions in the IoT based on Systematic Literature Review (SLR). The main goal of this SLR-based overview is to recognize significant research trends in the field of energy management and power consumption techniques which need additional consideration to highlight more efficient and effective methods in IoT. Also, a taxonomy is proposed to categorize the existing research studies on energy management solutions. A statistical and technical analysis of reviewed existing papers are provided, and evaluation factors and attributes are discussed. We observed that variety of published research papers in smart home have highest percentage to evaluate energy management in the IoT. Also, deep learning and clustering methods are must popular techniques that were applied to evaluate the energy management in IoT case studies. Finally, new challenges and forthcoming issues of the energy management and efficient power consumption methods are presented.