Subjects: Psychology >> Cognitive Psychology submitted time 2024-04-28
Abstract： This study used event related potential (ERP) technology to investigate the effects of different types of unitization on item recognition in both younger and older adults through two experiments. A total of two theoretical accounts concern the role of unitization in both item and associative recognition: “benefits and costs” and “benefits-only” accounts. This study hypothesized that because young adults have more cognitive resources, either type of unitization with different demands on cognitive resources does not impair their item memory. However, older adults have fewer cognitive resources, and whether different types of unitization impair their item memory depends on how these demand cognitive resources. Experiment 1 manipulated the level of bottom-up unitization by using compound words and unrelated words. Experiment 2 manipulated the level of top-down unitization using definition and sentence.
In experiment 1, a total of 19 community-dwelling older and 23 younger adults were asked to learn compound and unrelated word pairs, and during tests, they were asked to perform item recognition and associative recognition tasks. In experiment 2, a total of 19 community-dwelling older adults and 20 younger adults were asked to learn word pairs under definition and sentence conditions, and during the test they were required to perform item recognition and associative recognition tasks. In our sample of two experiments, all Older adults completed the mini mental state examination and scored at least 26 points
For younger adults, two types of unitization condition had no effect on their associative and item recognition. The ERP results of Experiment 1 revealed a comparable frontal old/new effect in both compound wordsand unrelated words condition, and the compound words condition reduced the parietal old/new effect. The ERP results of Experiment 2 indicated that the frontal old/new effect was absent in the definition condition, and both unitization conditions revealed a comparable the parietal old/new effect. For older adults, two types of unitization enhanced their associative recognition, however, have different influence on the item recognition. The behavioral results of Experiment 1 showed that older adults’ item recognition performance under the compound words condition was superior to that under the unrelated words condition. The ERP results indicated that the frontal old/new effect was only present in the compound words condition, and both encoding conditions revealed a comparable the parietal old/new effect. The behavioral results of Experiment 2 showed that older adults’ item recognition performance under the definition condition was inferior to that under the sentence condition. The ERP results revealed that the frontal old/new effect was absent in definition condition and only present in the sentence condition, and both encoding conditions were found to have comparable parietal old/new effect.
The influence of unitization on the item recognition depends on the encoding types. For younger adults, the item recognition in both unitized encoding conditions were comparable to that in the non-unitized encoding. Equivalent levels of memory retrieval were achieved through “less” overall neural processing on familiarity or recollection, which supports the “benefits-only” account. For older adults, the bottom-up unitized encoding condition promotes item recognition relying on the frontal old/new effects, which supports the “benefits-only” account. The top-down unitized encoding condition impaired older adults’ item recognition relying on the absent of the frontal old/new effects, which supports the “benefits and costs” account.
Subjects: Psychology >> Psychological Measurement submitted time 2023-11-22
Abstract： Cognitive diagnostic computerized adaptive testing (CD-CAT) provides a detailed diagnosis of an examinee’s strengths and weaknesses in the content measured in a timely and accurate manner, which can be used as a reference for further study or remediation planning, thus meeting the practical need for efficient and detailed test results. The successful implementation of CD-CAT is based on an item bank, but its maintenance is a very challenging task. A psychometrically popular choice for maintaining an item bank is online calibration. Currently, the research on online calibration methods in the CD-CAT that can calibrate Q-matrix and item parameters simultaneously is very weak. The existing methods are basically developed based on the deterministic input, noisy and gate (DINA) model. Compared with the DINA model, the generalized DINA (G-DINA) model has been more widely applied because it is less restrictive and can meet the requirements of a large number of test data in psychological and educational assessment. Therefore, if the online calibration method that jointly calibrates the Q-matrix and item parameters can be developed for models with few constraints such as G-DINA, its meaning is understood without explanation.
In current study, a new online calibration method, SCADOCM, was proposed, which was suitable for the G-DINA model. The construction of SCADOCM was based on the smoothly clipped absolute deviation penalty (SCAD) and marginalized maximum likelihood estimation (MMLE/EM) algorithm. For the new item j, the log-likelihood function with SCAD can be formulated based on the examinees’ responses in this item and the examinees’ attribute marginal mastery probability, and the q-vector of the new item can be estimated by the q-vector estimator based on SCAD. Then, the EM algorithm was used to estimate the item parameter of the new item j based on the posterior distributions of examinees’ attribute patterns, the examinees’ responses to new item j and the estimated q-vector.
To examine the performance of the proposed SCADOCM and compare it with the SIE method, two simulation studies (Study 1 and Study 2) are conducted. Study 1 is based on a simulated item bank while Study 2 is based on the real item bank (Internet addiction item bank; Shi, 2017). In these simulation studies, four factors were manipulated: the calibration sample size (nj = 50 vs. 100 vs. 500 vs. 1000 vs. 2000), the distribution of the attribute pattern (uniform distribution vs. high-order distribution vs. normal distribution), the item quality (U (0.05, 0.15) vs. U (0.1, 0.3)), and the online calibration methods (SCADOCM vs. SIE). The results showed that (1) SCADOCM has satisfactory calibration accuracy and calibration efficiency, and is superior to the SIE method. In addition, the traditional SIE method is not applicable for the G-DINA model, and its Q-matrix estimation accuracy rate is low under all experimental conditions. (2) The item calibration accuracy of SCADOCM and SIE increases with the increase of calibration sample and item quality under most conditions, and its item calibration accuracy in the uniform distribution/higher-order distribution is greater than that in the normal distribution. (3) The calibration efficiency of SCADOCM decreases with the increase of calibration samples, but it is less affected by the item quality and the attribute pattern distribution; the calibration efficiency of SIE decreases with the increase of calibration samples, but it is less affected by the item quality. Moreover, the calibration efficiency of the SIE method in the normal distribution is slightly slower than that of uniform distribution/high-order distribution.
To sum up the results, this study demonstrated that the SCADOCM has higher item calibration accuracy and calibration efficiency, and outperforms the SIE method; meanwhile, the traditional SIE method is not suitable for G-DINA model. All in all, this study provides an efficient and accurate method for item calibration in CD-CAT, and provides important support for further promoting the application of CD-CAT in practice.
Subjects: Psychology >> Cognitive Psychology submitted time 2022-04-25
Abstract：认知控制的主要研究范式之一是任务切换。以往研究发现切换代价受到认知控制层级性的调节，但鲜有研究探索这一调节过程的动态神经机制。本研究通过嵌套的线索-任务切换范式考察不同层级任务切换代价的差异及其神经机制。在实验中，要求被试完成高低两种层级任务，低层级任务要求被试判断数字大小（或奇偶）；高层级任务则须先加工数字的某一语义特征（如当前数字是否是偶数），然后进行大小判断。行为结果表明，高层级任务切换代价显著大于低层级任务切换代价。线索锁时的脑电结果表明，层级效应最早出现于P2成分，切换效应（切换与重复之差）在CNV成分上受到任务层级的调控，反映了在任务目标重构阶段给予高层级任务更多的选择性注意以及更高的主动性控制。目标锁时的脑电结果表明，在N2及慢波（SP）成分上，高层级任务切换与重复的波幅差异相比低层级任务显著更大，反映了在抑制旧任务集与重构新反应集的过程中增强的反应性控制。这些结果为任务设置重构论和认知控制的层级性提供了新的证据。
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2020-09-02
Abstract： " Existing literature has shown that dual-objective CD-CAT testing can facilitate the achievement of measurement objectives for both formative and summative assessments. And the Gini Index can be used as a measurement for the degree of uncertainty of random variables since a smaller Gini value indicates a lower degree of uncertainty. Hence, this paper proposed a Gini-Index-based selection method for dual-objective CD-CAT, and it measured the changes in the posterior probability of knowledge state and confidence interval for latent traits estimation. By adopting the Bayesian Decision Theory, the potential information of participants could be detected based on participants’ responses and changes in posterior probability distribution of two the random variables. Monte Carlo Simulation was used to test the performances of the selection method based on Gini, ASI, IPA and JSD, respectively. The item banks measured 5 attributes consisting of 250 items in total, and each item measured 3 attributes at most. The true knowledge state of each participant was generated by HO-CDM and Multivariate Normal Models (both means were 0 and covariance coefficient was 0.8 and 0.2, respectively). G-DINA, DINA and R-RUM were adopted as the cognitive diagnostic models and the item bank of each of these three models included both CDM and 2PL parameters. Specifically, CDM parameters were generated by a G-DINA package in R software with the slipping and guessing parameters randomly selected from uniform distribution in a range from 0.05 to 0.25. The 2PL parameters were estimated by factoring in the responses elicited from 3,000 participants’ responses to all items in item banks using the mirt package. Four indexes, namely the pattern measurement rates, root mean square error of latent trait, chi-square value and time needed for item selection, were adopted in comparing the efficiency of different item selection methods. The value for each index was the mean of 10 repeated simulations of 1,000 participants’ responses to all item bank. The results showed that (1) The Gini and IPA selection methods had similar performance in terms of pattern measurement rates, root mean square error of latent trait and chi-square value. Both methods were high in precision measurement and low in sensitivity to CDM and the distribution of participants’ cognitive patterns, making both methods applicable to the item banks featuring a mixture of cognitive diagnosis models. By comparison, the Gini method outperformed slightly the IPA method in pattern measurement rates and time needed for item selection in which the Gini method was only one-tenth that of the IPA method; (2) Both the Gini and ASI selection methods were weighted linear combination approaches. The performances of the two methods were very close in the short test. In the long test, however, although time needed for item selection using the ASI method was only one-third that of the Gini method, the latter was superior to the former in terms of measurement accuracy and chi-square value; (3) Although the JSD method outperformed the Gini method in terms of uniformity of item bank usage and time needed for item selection, its measurement accuracy was far less than the latter. To summarize, the Gini, IPA and ASI selection methods all have good measurement accuracy and hence are all recommended for short tests. For medium and long tests with a limited number of attributes and a smaller item bank, the Gini and IPA selection methods are recommended. As the number of attributes and item bank size grow, the Gini method is recommended. When there are high correlations among different attributes, as well as a large number of attributes and big item bank size, the ASI and JSD selection methods are recommended with the ASI method slightly outperforming the JSD method in measurement accuracy.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2020-08-21
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2020-05-12
Abstract：变点分析法(change point analysis, CPA)近些年才引入心理与教育测量学，相较于传统方法，CPA不仅可以侦查异常作答被试，还能自动精确地定位变点位置，高效清洗作答数据。其原理在于：判断作答序列中是否存在可将该序列划分为具有不同统计学属性两部分的点(即变点)，并且需使用被试拟合统计量(person-fit statistic, PFS)来量化两个子序列之间的差异。未来可将单变点分析拓展至多变点，结合反应时等信息，构建非参数化指标以及将现有指标拓展至多级计分或多维测验，以提高CPA的适用广度及效力。
Subjects: Psychology >> Cognitive Psychology submitted time 2020-05-07
Abstract： Scanmatch is an emerging method of eye movement data analysis in recent years. The method includes four steps of preprocessing of gaze data, division and encoding of interest regions, formation of eye track strings, and calculation of similarity scores. The researcher used scanmatch to study the decision process theory and related influencing factors, and verified the feasibility and accuracy of scanmatch in the decision research field. Future research should use scanmatch to conduct in-depth research on various decision-making theories and influencing factors to reveal the essence of decision-making process and construct a more complete decision theory model. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2020-04-19
Abstract： The outbreak of the COVID-19 in Wuhan China has characterized as a "pandemic" by WHO as the virus spreads increasingly worldwide. As the worst public health incident since new millennium, the COVID-19 is severely threatening human's health and lives. At the same time, the epidemic of COVID-19 has also caused worry and panic among the affected people. A series of chain reactions caused by this negative emotion will further aggravate the destructiveness of the epidemic of COVID-19. Therefore, providing psychological and social support to the people affected by the epidemic event and meeting their psychological and social needs can effectively help the affected people to gradually resume normal social life, improve satisfaction and comfort, and get them out of the epidemic as soon as possible. As General Secretary Xi Jinping pointed out,“The current situation of epidemic prevention and control is severe and complicated. Some people have anxiety and fear. Publicity and public opinion work must be strengthened to guide people to increase their confidence, strengthen their confidence, and focus on stabilizing the public’ s mood.” This study explored the impact of the public's epidemic risk perception on their protective behavior, and the mediating role of social trust and coping efficacy between the public's epidemic risk perception and protective behavior during the outbreak of the COVID-19. The results found that:(1)The public's epidemic risk perception is at a moderately high level, and the public has taken proactive protective actions against the COVID-19. (2)The public's affective risk perception social support have a direct predictive effect on the protective behaviors of positive actions and the plan to solve. (3)The public's social trust and coping efficacy play a partial mediating role between affective risk perception and protective behavior; The public's social trust and coping efficacy play a complete mediating role between cognitive risk perception and protective behavior; The public's social trust and coping efficacy play a partial mediating role between social support and protective behavior.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2020-03-04
Abstract： This project aims to investigate psychological mechanisms of behavioral poverty trap in China, and hence put forward corresponding risk management strategies. For this purpose, we intend to draw on the new research paradigm in poverty study, which is initiated by behavioral economists, and recruit residents who live in extreme poor areas as participants. First, a framework concerning both the cognitive and motivational base of behavioral poverty trap is proposed as empirical and theoretical route of this project. Second, we analyze how cognitive outcomes of poverty psychologically and neurally affect subsequent decision behavior, as well as how both cognitive and motivational outcomes of poverty jointly influence subsequent decision behavior. In addition, the casual effect of psychological outcomes caused by poverty on subsequent decision behavior is empirically examined. Third, we further conduct randomized controlled experiments to understand the influence of cognitive changes caused by poverty on subsequent decision behavior, as well as field intervention studies to test the effect of self-identity changes caused by poverty on subsequent decision behavior. Based on these empirical researches, management strategies for poverty alleviation are discussed.
Subjects: Psychology >> Cognitive Psychology submitted time 2020-02-26
Abstract： " This project aims to investigate psychological mechanisms of behavioral poverty trap in China, and hence put forward corresponding risk management strategies. For this purpose, we intend to draw on the new research paradigm in poverty study, which is initiated by behavioral economists, and recruit residents who live in extreme poor areas as participants. First, a framework concerning both the cognitive and motivational base of behavioral poverty trap is proposed as empirical and theoretical route of this project. Second, we analyze how cognitive outcomes of poverty psychologically and neurally affect subsequent decision behavior, as well as how both cognitive and motivational outcomes of poverty jointly influence subsequent decision behavior. In addition, the casual effect of psychological outcomes caused by poverty on subsequent decision behavior is empirically examined. Third, we further conduct randomized controlled experiments to understand the influence of cognitive changes caused by poverty on subsequent decision behavior, as well as field intervention studies to test the effect of self-identity changes caused by poverty on subsequent decision behavior. Based on these empirical researches, management strategies for poverty alleviation are discussed. "
Subjects: Psychology >> Psychological Measurement submitted time 2019-09-16
Abstract： Cognitive diagnostic assessments (CDAs) can provide fine-grained diagnostic information about students' knowledge states, so as to help to teach in accordance with the students’ aptitude. The development of cognitive diagnosis model for polytomous response data expands the application scope of cognitive diagnostic assessment. As the basis of CDAs, Q-matrix has aroused more and more attention for the subjective tendency in Q-matrix construction that is typically performed by domain experts. Due to the subjective process of Q-matrix construction, there inevitably have some misspecifications in the Q-matrix, if left unchecked, can result in a serious negative impact on CDAs. To avoid the subjective tendency from experts and to improve the correctness of the Q-matrix, several objective Q-matrix validation methods have been proposed. Many Q-matrix validation methods have been proposed in dichotomous CDMs, however, the research of the Q-matrix validation method under polytomous CDMs is stalling lacking. To address this concern, several relative fit statistics (i.e., -2LL, AIC, BIC) were applied to the Q-matrix validation for polytomous cognitive diagnosis model in this research. The process of Q-matrix validation is as follows: First, the reduced Q-matrix is represented by , which represents a set of potential q-vectors and contains possible q-vectors when attributes are independent. When validating the q-vector of the first category of item j, all possible q-vectors in can be used as the q-vector of the first category of item j, and the Q-matrix of remaining items remains intact. From this, the item parameters and the attribute patterns of students can be estimated, and the -2LL, AIC, and BIC can be calculated accordingly. The q-vector with the largest likelihood (or smallest AIC/BIC) is regarded as the q-vector of the first category of item j. The q-vector of the next category of the item j can also be obtained in the same way. The algorithm stops when the validated Q-matrix is same as the previous Q-matrix, or every item has been reached. In order to improve the efficiency of the method, a sequential search algorithm was proposed. Several simulation studies were conducted to evaluate the effectiveness and practicality of these methods, and the performance of the methods in this paper was compared with the stepwise method (Ma & de la Torre, 2019). Three experimental factors were considered in simulation studies, including sample size, Q-matrix error types and CDMs. The results show that (1) BIC method can be used for Q-matrix validation under polytomous response CDMs, and the performance of the BIC method is better than the stepwise method. (2) In general, the performance of the three methods from good to bad is the BIC method, AIC method, and -2LL method. (3) The performance of Q-matrix validation methods is affected by the sample size, and increasing the number of sample size can improve the accuracy of the Q-matrix validation. In this study, Q-matrix validation methods for polytomous response CDMs were studied. It was found that the BIC method can be used for the Q-matrix validation under polytomous response CDMs. The method proposed in this paper can not only improve the accuracy of Q-matrix specification but also increase the model-data fit level. Besides, the data-based Q-matrix validation method can also reduce the workload of experts in Q-matrix construction and improve the classification accuracy of cognitive diagnosis. " " " " "
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