心理因素与学业表现：机器学习分类预测模型

随着高等教育规模的扩大,学业表现不良逐渐成为一个不容忽视的现象,对学业表现不良的学生进行预测并提早给予干预可降低退学率并减少教育资源的损失。由于导致学业表现不良的因素众多且关系复杂,传统的基于相关分析的研究方法很难建立早期预测模型并进行应用。本研究旨在利用机器学习算法,对数据进行挖掘,并建立学业表现预测模型。研究对653名大一新生的心理健康状况、应对方式、人格、内外控倾向和相关人口统计学信息进行了收集,并在一年后采集了其学业成绩,利用随机森林(RF)、K邻近（KNN）、支持向量机（SVM）、决策树（DT）、朴素贝叶斯（NB）等机器学习算法建立了分类模型。结果显示,随机森林算法在识别学业表现不良学生时有最好的表现,其中准确率95.86%, 召回率91.83%,f1分数为93.80%。特征重要性分析显示,前10个对模型有最高贡献度的特征包括：年龄、性别、是否为独生子、内外控倾向、神经质倾向、积极应对倾向、宜人性倾向、一般症状指数、开放性倾向和焦虑水平。为避免过度拟合问题,本研究在一年后收集的166名新生样本中进行了模型验证,结果显示模型在新数据集上有较好的泛化表现,其中f1分数90.90％,准确率92.60％,召回率89.26％。研究提示基于人口统计学和心理测评信息,机器学习算法有助于及早识别学业表现不良学生并为开展早期干预提供启示。     

A systematic review of the effectiveness of machine learning for predicting psychosocial outcomes in acquired brain injury: Which algorithms are used and why?

Clinicians working in the field of acquired brain injury (ABI, an injury to the brain sustained after birth) are challenged to develop suitable care pathways for an individual client’s needs. Being able to predict psychosocial outcomes after ABI would enable clinicians and service providers to make advance decisions and better tailor care plans. Machine learning (ML, a predictive method from the field of artificial intelligence) is increasingly used for predicting ABI outcomes. This review aimed to examine the efficacy of using ML to make psychosocial predictions in ABI, evaluate the methodological quality of studies, and understand researchers’ rationale for their choice of ML algorithms. Nine studies were reviewed from five databases, predicting a range of psychosocial outcomes from stroke, traumatic brain injury, and concussion. Eleven types of ML were employed with a total of 75 ML models. Every model was evaluated as having high risk of bias, unable to provide adequate evidence for predictive performance due to poor methodological quality. Overall, there was limited rationale for the choice of ML algorithms and poor evaluation of the methodological limitations by study authors. Considerations for overcoming methodological shortcomings are discussed, along with suggestions for assessing the suitability of data and suitability of ML algorithms for different ABI research questions.     

The Natural Selection of Prediction Heuristics: Anchoring and Adjustment versus Representativeness

There are several heuristics which people use in making numerical predictions and these heuristics compete for the determination of prediction output. Some of them (e.g. representativeness) lead to excessively extreme predictions while others (e.g. anchoring and adjustment) lead to regressive (and even over-regressive) predictions. In this paper we study the competition between these two heuristics by varying the representation of predictor and outcome. The results indicate that factors which facilitate reliance on representativeness (e.g. compatibility between predictor and outcome) indeed lead to an increase in extremity, while factors that facilitate reliance on anchoring and adjustment (e.g. increased salience of a potential anchor) lead to a decrease in extremity.     

Too exhausted to go to bed: Implicit theories about willpower and stress predict bedtime procrastination

While most people are aware of the importance of sleep for their health, well-being, and performance, bedtime procrastination is a pervasive phenomenon that can be conceptualized as a case of self-control failure (Kroese et al., Frontiers in Psychology, 5, 2014, 1). Two daily diary studies (N₁ = 185, N₂ = 137) investigated beliefs about willpower and stress as interactive predictors of bedtime procrastination. Beliefs about willpower capture whether people think of their willpower as limited resource that gets easily depleted (limited theory) or as something that remains regardless of previous acts of self-control (non-limited theory). Results show that after a stressful day, people with a limited versus non-limited theory procrastinate more on going to bed, while there is no difference in bedtime procrastination on less stressful days. Thus, ironically, limited theorists who should be more concerned with recovering their resources after a stressful day sleep less the following night.     

Creation and humanity: Veli-Matti Kärkäinen's answer to the ultimate question

This article focuses on the third volume of Vel-Matti Kärkkäinen's systematic theology, titled Creation and Humanity. After a brief overview of the volume the article offers some clarification on the tenth chapter, especially on its interaction with paleontology. After that, two constructive observations follow. The first is related to Kärkkäinen's notion of the embeddedness of human nature, and the second is to further employ systems thinking in his constructive work on creation and human evolution.     

The return of the repressed. On Robert N. Bellah,Norman O. Brown,and religion in human evolution

As much as Robert Bellah’s final work, Religion in Human Evolution, has been studied and dissected, no critic underlined the importance of psychoanalysis for its main argument and its theoretical framework. The paper shows the influence exerted by a controversial interpreter of Freud, Norman O. Brown, on Bellah’s ideas, intellectual profile, and writing style in the late-1960s and early 1970s. While in search for a new intellectual voice, Bellah was struck by Brown’s work and began to make intensive use of his book, Love’s Body, both in his teaching and in his research of the early 1970s, during his so-called “symbolic realism” period. While Bellah abandoned Brown’s ideas and style in the mid-1970s, some of the basic intuitions he had during that period still survived as one of the major theoretical intuitions of Religion and Human Evolution.     

ON THE BENEFITS OF PHILOSOPHY AS A WAY OF LIFE IN A GENERAL INTRODUCTORY COURSE

Philosophy as a way of life (PWOL) places investigations of value, meaning, and the good life at the center of philosophical investigation, especially of one’s own life. This essay argues that PWOL is compatible with general introductory philosophy courses, further arguing that PWOL-based general introductions have several philosophical and pedagogical benefits. These include the ease with which high-impact practices, situated skill development, and students’ ability to “think like a disciplinarian” may be incorporated into such courses, relative to more traditional introductory courses, as well as the demonstration of philosophy’s value to students by explicitly tying philosophical investigation to students’ own lives.     

Geographic patterns of implicit age bias and associations with state-level health outcomes across the United States

Negative attitudes toward aging are pervasive in society and may be detrimental to people's health as they become older. Older people tend to report feeling significantly younger than their chronological age, often as a way of psychologically distancing themselves from the stigma of old age. However, attitudes and behaviors toward aging may differ across regional contexts. We examined associations among state-level patterns of bias against older adults and state-level health outcomes across the United States. Data from 803,009 respondents (ages: 15–94) across 50 U.S. states (and the District of Columbia) revealed geographic variation in implicit age bias. Higher state-level implicit age bias was associated with poorer state-level health outcomes among adults ages 65+. Older adults living in states high in implicit age bias showed greater age-group dissociation compared to older adults living in states low in implicit age bias. Findings highlight potential consequences of implicit age bias and invite further research on the long-term health implications of individual age-group dissociation in response to regional age bias.     

Quantifying the Interplay of Semantics and Phonology During Failures of Word Retrieval by People With Aphasia Using a Multiplex Lexical Network

Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by people with Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia.